@inproceedings{zhai2020piggyback,
  author       = {Mengyao Zhai and
                  Lei Chen and
                  Jiawei He and
                  Megha Nawhal and
                  Frederick Tung and
                  Greg Mori},
  title        = {Piggyback {GAN:} Efficient Lifelong Learning for Image Conditioned
                  Generation},
  booktitle    = {Proceedings of the 16th European Conference on Computer Vision (ECCV), Part {XXI}}, 
  address     = {Glasgow,
                  UK},
  pages        = {397--413},
  year         = {2020}
}

@article{popel2020transforming,
  title={Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals},
  author={Popel, Martin and Tomkova, Marketa and Tomek, Jakub and Kaiser, {\L}ukasz and Uszkoreit, Jakob and Bojar, Ond{\v{r}}ej and {\v{Z}}abokrtsk{\`y}, Zden{\v{e}}k},
  journal={Nature communications},
  volume={11},
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  pages={4381},
  year={2020},
  publisher={Nature Publishing Group UK London}
}
@article{song2019abstractive,
  title={Abstractive text summarization using LSTM-CNN based deep learning},
  author={Song, Shengli and Huang, Haitao and Ruan, Tongxiao},
  journal={Multimedia Tools and Applications},
  volume={78},
  pages={857--875},
  year={2019},
  publisher={Springer}
}
@inproceedings{vaswani2018tensor2tensor,
  author       = {Ashish Vaswani and
                  Samy Bengio and
                  Eugene Brevdo and
                  Fran{\c{c}}ois Chollet and
                  Aidan N. Gomez and
                  Stephan Gouws and
                  Llion Jones and
                  Lukasz Kaiser and
                  Nal Kalchbrenner and
                  Niki Parmar and
                  Ryan Sepassi and
                  Noam Shazeer and
                  Jakob Uszkoreit},
  title        = {Tensor2Tensor for Neural Machine Translation},
  booktitle    = {Proceedings of the 13th Conference of the Association for Machine
                  Translation in the Americas (AMTA)},
   address    = {Boston, MA},
  pages        = {193--199},
  year         = {2018}
}

@inproceedings{prakash2016neural,
  author       = {Aaditya Prakash and
                  Sadid A. Hasan and
                  Kathy Lee and
                  Vivek V. Datla and
                  Ashequl Qadir and
                  Joey Liu and
                  Oladimeji Farri},
  title        = {Neural Paraphrase Generation with Stacked Residual {LSTM} Networks},
  booktitle    = {Proceedings of the 26th International Conference on Computational Linguistics (COLING)},
  address     = {Osaka, Japan},
  pages        = {2923--2934},
  year         = {2016}
}

@article{serban2016generative,
  title={Generative deep neural networks for dialogue: A short review},
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  year={2016}
}
@inproceedings{cai2019retrieval,
  title={Retrieval-guided dialogue response generation via a matching-to-generation framework},
  author={Cai, Deng and Wang, Yan and Bi, Wei and Tu, Zhaopeng and Liu, Xiaojiang and Shi, Shuming},
  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
  pages={1866--1875},
  year={2019},
 address = {Hong Kong, China}  
}
@article{yang2020survey,
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  year={2020}
}
@article{lin2020variational,
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  year={2020}
}
@inproceedings{yin2015convolutional,
  author       = {Wenpeng Yin and
                  Hinrich Sch{\"{u}}tze},
  title        = {Convolutional Neural Network for Paraphrase Identification},
  booktitle    = {Proceedings of the 2015 Conference of the North American Chapter
                  of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)},
  address     = {Denver, CO},
  pages        = {901--911},
  year         = {2015}
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@article{esteva2021covid,
  title={COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization},
  author={Esteva, Andre and Kale, Anuprit and Paulus, Romain and Hashimoto, Kazuma and Yin, Wenpeng and Radev, Dragomir and Socher, Richard},
  journal={NPJ digital medicine},
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  number={1},
  pages={68},
  year={2021},
  publisher={Nature Publishing Group UK London}
}
@article{malinowski2017ask,
  title={Ask your neurons: A deep learning approach to visual question answering},
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  volume={125},
  pages={110--135},
  year={2017},
  publisher={Springer}
}
@article{sharma2018deep,
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  year={2018},
  publisher={Elsevier}
}
@inproceedings{gupta2018deep,
  author       = {Ankush Gupta and
                  Arvind Agarwal and
                  Prawaan Singh and
                  Piyush Rai},
  title        = {A Deep Generative Framework for Paraphrase Generation},
  booktitle    = {Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence (AAAI)},
  address    = {New Orleans, LA},
  pages        = {5149--5156},
  year         = {2018}
}



@inproceedings{chang2021towards,
  author       = {Heng{-}Jui Chang and
                  Hung{-}yi Lee and
                  Lin{-}Shan Lee},
  title        = {Towards Lifelong Learning of End-to-End {ASR}},
  booktitle    = {Proceedings of the 22nd Annual Conference of the International Speech
                  Communication Association (Interspeech)},
  address      = {Brno, Czechia},
  pages        = {2551--2555},
  year         = {2021}
}

@article{liu2019unsupervised,
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  year={2019}
}
@inproceedings{singh2017machine,
  title={Machine translation using deep learning: An overview},
  author={Singh, Shashi Pal and Kumar, Ajai and Darbari, Hemant and Singh, Lenali and Rastogi, Anshika and Jain, Shikha},
  booktitle={Proceedings of the 2017 international conference on computer, communications and electronics (comptelix)},
  pages={162--167},
  year={2017}
}
@article{ma2022multi,
  title={Multi-document summarization via deep learning techniques: A survey},
  author={Ma, Congbo and Zhang, Wei Emma and Guo, Mingyu and Wang, Hu and Sheng, Quan Z},
  journal={ACM Computing Surveys},
  volume={55},
  number={5},
  pages={1--37},
  year={2022},
  publisher={ACM New York, NY}
}
@article{yousefi2017text,
  title={Text summarization using unsupervised deep learning},
  author={Yousefi-Azar, Mahmood and Hamey, Len},
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  volume={68},
  pages={93--105},
  year={2017},
  publisher={Elsevier}
}
@article{santhanam2019survey,
  title={A survey of natural language generation techniques with a focus on dialogue systems-past, present and future directions},
  author={Santhanam, Sashank and Shaikh, Samira},
  journal={arXiv preprint arXiv:1906.00500},
  year={2019}
}
@inproceedings{nekoei2021continuous,
  author       = {Hadi Nekoei and
                  Akilesh Badrinaaraayanan and
                  Aaron C. Courville and
                  Sarath Chandar},
  editor       = {Marina Meila and
                  Tong Zhang},
  title        = {Continuous Coordination As a Realistic Scenario for Lifelong Learning},
  booktitle    = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
  address    = {Virtual Event},
  pages        = {8016--8024},
  year         = {2021}
}

@inproceedings{sarnen2020lifelong,
  title={Lifelong Learning for Dynamic Churn Prediction},
  author={Sarnen, Fioni and Suyanto, Suyanto and Rismala, Rita},
  booktitle={Proceedings of the 2020 International Conference on Data Science and Its Applications (ICoDSA)},
  pages={1--5},
  year={2020}
}
@inproceedings{yang2022evaluations,
  author       = {Fan Yang and
                  Chao Yang and
                  Huaping Liu and
                  Fuchun Sun},
  title        = {Evaluations of the Gap between Supervised and Reinforcement Lifelong
                  Learning on Robotic Manipulation Tasks},
  booktitle    = {Proceedings of the Conference on Robot Learning (CoRL)}, 
  address     = {London, {UK}},
  pages        = {547--556},
  year         = {2021}
}

@article{febrinanto2023graph,
  title={Graph lifelong learning: A survey},
  author={Febrinanto, Falih Gozi and Xia, Feng and Moore, Kristen and Thapa, Chandra and Aggarwal, Charu},
  journal={IEEE Computational Intelligence Magazine},
  volume={18},
  number={1},
  pages={32--51},
  year={2023},
  publisher={IEEE}
}
@article{van2018generative,
  title={Generative replay with feedback connections as a general strategy for continual learning},
  author={Van de Ven, Gido M and Tolias, Andreas S},
  journal={arXiv preprint arXiv:1809.10635},
  year={2018}
}
@article{kirkpatrick2017overcoming,
  title={Overcoming catastrophic forgetting in neural networks},
  author={Kirkpatrick, James and Pascanu, Razvan and Rabinowitz, Neil and Veness, Joel and Desjardins, Guillaume and Rusu, Andrei A and Milan, Kieran and Quan, John and Ramalho, Tiago and Grabska-Barwinska, Agnieszka and others},
  journal={Proceedings of the national academy of sciences},
  volume={114},
  number={13},
  pages={3521--3526},
  year={2017},
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}
@article{holla2020meta,
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  year={2020}
}
@inproceedings{zhao2022prompt,
  author       = {Yingxiu Zhao and
                  Yinhe Zheng and
                  Zhiliang Tian and
                  Chang Gao and
                  Jian Sun and
                  Nevin L. Zhang},
  title        = {Prompt Conditioned {VAE:} Enhancing Generative Replay for Lifelong
                  Learning in Task-Oriented Dialogue},
  booktitle    = {Proceedings of the 2022 Conference on Empirical Methods in Natural
                  Language Processing (EMNLP)},
  address     = {Abu Dhabi, United Arab Emirates},
  pages        = {11153--11169},
  year         = {2022}
}

@inproceedings{isele2018selective,
  author       = {David Isele and
                  Akansel Cosgun},
  title        = {Selective Experience Replay for Lifelong Learning},
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  address     = {New Orleans, LA},
  pages        = {3302--3309},
  year         = {2018}
}

@inproceedings{zhou2021overcoming,
  author       = {Fan Zhou and
                  Chengtai Cao},
  title        = {Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience
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  booktitle    = {Proceedings of. theThirty-Fifth {AAAI} Conference on Artificial Intelligence (AAAI)},
  address     = {Virtual Event},
  pages        = {4714--4722},
  year         = {2021}
}
@inproceedings{DBLP:conf/annpr/ZacariasA18,
  author       = {Abel S. Zacarias and
                  Lu{\'{\i}}s A. Alexandre},
  editor       = {Luca Pancioni and
                  Friedhelm Schwenker and
                  Edmondo Trentin},
  title        = {SeNA-CNN: Overcoming Catastrophic Forgetting in Convolutional Neural
                  Networks by Selective Network Augmentation},
  booktitle    = {Artificial Neural Networks in Pattern Recognition - 8th {IAPR} {TC3}
                  Workshop, {ANNPR} 2018, Siena, Italy, September 19-21, 2018, Proceedings},
  series       = {Lecture Notes in Computer Science},
  volume       = {11081},
  pages        = {102--112},
  publisher    = {Springer},
  year         = {2018},
  url          = {https://doi.org/10.1007/978-3-319-99978-4\_8},
  doi          = {10.1007/978-3-319-99978-4\_8},
  timestamp    = {Sun, 02 Jun 2019 21:21:37 +0200},
  biburl       = {https://dblp.org/rec/conf/annpr/ZacariasA18.bib},
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@article{de2022continual,
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  author={De Lange, Matthias and van de Ven, Gido and Tuytelaars, Tinne},
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  year={2022}
}

@inproceedings{yin2022learning,
  author       = {Haiyan Yin and
                  Dingcheng Li and
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  booktitle    = {Proceedings of the 2022 Conference of the North American Chapter of
                  the Association for Computational Linguistics: Human Language Technologies (NAACL)},
  address      = {Seattle, WA},
  pages        = {1385--1395},
  year         = {2022}
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@inproceedings{shu2017lifelong,
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  title        = {Lifelong Learning {CRF} for Supervised Aspect Extraction},
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  address      = {Vancouver, Canada},
  pages        = {148--154},
  year         = {2017}
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@inproceedings{yin2021mitigating,
  author    = {Haiyan Yin and
               Peng Yang and
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  address   = {virtual},
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  year      = {2021}
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  year      = {2021},

}


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@inproceedings{shrivastava2014densifying,
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@inproceedings{li2014coding,
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@inproceedings{shrivastava2014asymmetric,
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@inproceedings{li2013sign,
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@inproceedings{li20150,
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@techreport{Report:Li_GMM16,
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@techreport{Report:Li_GMM_Nys16,
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@inproceedings{shrivastava2015asymmetric,
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@inproceedings{li2019random,
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@inproceedings{shrivastava2016simple,
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@inproceedings{yu2017greedy,
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@inproceedings{cui2018neural,
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@inproceedings{etzioni2011open,
  author    = {Oren Etzioni and
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@inproceedings{fader2011identifying,
  author    = {Anthony Fader and
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  title     = {An Empirical Evaluation of {GDPR} Compliance Violations in Android
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@article{guaman2021gdpr,
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               Viktor Kuncak},
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@article{hasan2021text2app,
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@inproceedings{kolluru2020imojie,
  author    = {Keshav Kolluru and
               Samarth Aggarwal and
               Vipul Rathore and
               Mausam and
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  title     = {{IMoJIE}: Iterative Memory-Based Joint Open Information Extraction},
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@inproceedings{li2018constructing,
  author    = {Zhongyang Li and
               Xiao Ding and
               Ting Liu},
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@article{linden2020privacy,
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               Stephen Soderland and
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               Michael Backes and
               Charles Weir and
               Sascha Fahl},
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               Communications Security (CCS)},
  address   = {Dallas, TX},
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  year      = {2017}
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@inproceedings{oltrogge2018rise,
  author    = {Marten Oltrogge and
               Erik Derr and
               Christian Stransky and
               Yasemin Acar and
               Sascha Fahl and
               Christian Rossow and
               Giancarlo Pellegrino and
               Sven Bugiel and
               Michael Backes},
  title     = {The Rise of the Citizen Developer: Assessing the Security Impact of
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  address   = {San Francisco, CA},
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  year      = {2018}
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@article{ro2020multi,
  author    = {Youngbin Ro and
               Yukyung Lee and
               Pilsung Kang},
  title     = {{Multi\({}^{\mbox{2}}\)OIE}: Multilingual Open Information Extraction
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@inproceedings{roy2019supervising,
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  year={2019}
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@inproceedings{saha2017bootstrapping,
  author    = {Swarnadeep Saha and
               Harinder Pal and
               Mausam},
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  year      = {2017}
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@inproceedings{schmitz2012open,
  author    = {Mausam and
               Michael Schmitz and
               Stephen Soderland and
               Robert Bart and
               Oren Etzioni},
  title     = {Open Language Learning for Information Extraction},
  booktitle = {Proceedings of the 2012 Joint Conference on Empirical Methods in Natural
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@inproceedings{shezan2020tkperm,
  author    = {Faysal Hossain Shezan and
               Kaiming Cheng and
               Zhen Zhang and
               Yinzhi Cao and
               Yuan Tian},
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  year      = {2020}
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@article{shezan2020verhealth,
  author    = {Faysal Hossain Shezan and
               Hang Hu and
               Gang Wang and
               Yuan Tian},
  title     = {VerHealth: Vetting Medical Voice Applications through Policy Enforcement},
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@inproceedings{stanovsky2018supervised,
  author    = {Gabriel Stanovsky and
               Julian Michael and
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  address   = {New Orleans, LA},
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  year      = {2018}
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  author    = {Mingming Sun and
               Xu Li and
               Ping Li},
  title     = {Logician and {Orator}: Learning from the Duality between Language and
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  booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural
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  address   = {Brussels, Belgium},
  pages     = {2119--2130},
  year      = {2018}
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@inproceedings{sun2018logician,
  author    = {Mingming Sun and
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               Xin Wang and
               Miao Fan and
               Yue Feng and
               Ping Li},
  title     = {Logician: {A} Unified End-to-End Neural Approach for Open-Domain Information
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  booktitle = {Proceedings of the Eleventh {ACM} International Conference on Web
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  address    = {Marina Del Rey, CA},
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  year      = {2018}
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@inproceedings{sun2020predicate,
  author    = {Mingming Sun and
               Wenyue Hua and
               Zoey Liu and
               Xin Wang and
               Kangjie Zheng and
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  title     = {{A Predicate-Function-Argument Annotation of Natural Language for Open-Domain
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  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural
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@inproceedings{tesfay2018read,
  author    = {Welderufael B. Tesfay and
               Peter Hofmann and
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  title     = {I Read but Don't Agree: Privacy Policy Benchmarking using Machine
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  booktitle = {Companion of the The Web Conference 2018 on The Web Conference 2018 (WWW)},
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@inproceedings{utz2019informed,
  author    = {Christine Utz and
               Martin Degeling and
               Sascha Fahl and
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@inproceedings{yu2015autoppg,
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  booktitle = {Proceedings of the 5th Annual {ACM} {CCS} Workshop on Security and
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@inproceedings{zhan2020span,
  author    = {Junlang Zhan and
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@inproceedings{zhao2022integrity,
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               Steven M. Bellovin},
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               N. Cameron Russell and
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               Benny Pinkas and
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  pages={481-492}, 
  keywords={dynamic programming;learning (artificial intelligence);pattern classification;SAND;change detection module;chunk boundary;classifier confidence;concept drift handling;concept evolution;data stream classifier;dynamic programming;semi-supervised framework;sliding window based techniques;Data mining;Data models;Dynamic programming;Electronic mail;Error analysis;Labeling;Training data;Classifier Confidence;Concept Drift;Dynamic Chunk}, 
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               Li Fei{-}Fei},
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@inproceedings{lee2018stacked,
  author    = {Kuang{-}Huei Lee and
               Xi Chen and
               Gang Hua and
               Houdong Hu and
               Xiaodong He},
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@inproceedings{lu2019vilbert,
  author    = {Jiasen Lu and
               Dhruv Batra and
               Devi Parikh and
               Stefan Lee},
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@inproceedings{tan2019lxmert,
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               Mohit Bansal},
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               Natural Language Processing {(EMNLP-IJCNLP)}},
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@inproceedings{li2020unicoder,
  author    = {Gen Li and
               Nan Duan and
               Yuejian Fang and
               Ming Gong and
               Daxin Jiang},
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  booktitle = {Proceedings of the  Thirty-Fourth {AAAI} Conference on Artificial Intelligence (AAAI)},
  address   = {New York, NY},
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  year      = {2020}
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@inproceedings{chen2020uniter,
  author    = {Yen{-}Chun Chen and
               Linjie Li and
               Licheng Yu and
               Ahmed El Kholy and
               Faisal Ahmed and
               Zhe Gan and
               Yu Cheng and
               Jingjing Liu},
  title     = {{UNITER:} UNiversal Image-TExt Representation Learning},
  booktitle = {Proceedings of the 16th European Conference on Computer Vision (ECCV), Part {XXX}},
  address   = {Glasgow,
               UK},
  pages     = {104--120},
  year      = {2020}
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@inproceedings{tan2020detecting,
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               Bryan Plummer and 
               Kate Saenko},
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  address   = {Online},
  year      = {2020}
}

@inproceedings{su2020vl,
  author    = {Weijie Su and
               Xizhou Zhu and
               Yue Cao and
               Bin Li and
               Lewei Lu and
               Furu Wei and
               Jifeng Dai},
  title     = {{VL-BERT:} Pre-training of Generic Visual-Linguistic Representations},
  booktitle = {Proceedings of the 8th International Conference on Learning Representations (ICLR)}, 
  address   = {Addis Ababa, Ethiopia},
  year      = {2020}
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@inproceedings{cho2020x,
  author    = {Jaemin Cho and 
               Jiasen Lu and 
               Dustin Schwenk and 
               Hannaneh Hajishirzi and 
               Aniruddha Kembhavi},
  title     = {{X-LXMERT}: Paint, Caption and Answer Questions with Multi-Modal Transformers},
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  year      = {2020}
}

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               Subhransu Maji},
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@inproceedings{gao2016compact,
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@article{huang2020aligning,
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@inproceedings{Kuang2018Stacked,
  author    = {Kuang{-}Huei Lee and
               Xi Chen and
               Gang Hua and
               Houdong Hu and
               Xiaodong He},
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@inproceedings{li2020oscar,
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@inproceedings{sun2019videobert,
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               Pratik Ringshia and
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@inproceedings{gan2020large,
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               Jingjing Liu},
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  year      = {2020}
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@inproceedings{li2020hero,
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               Yen{-}Chun Chen and
               Yu Cheng and
               Zhe Gan and
               Licheng Yu and
               Jingjing Liu},
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  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural
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  year      = {2020}
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@inproceedings{zhu2020actbert,
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@inproceedings{lu2021visualsparta,
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@inproceedings{sun2021lightningdot,
  author    = {Siqi Sun and
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  pages={3270--3278},
  year={2015},
  address={Boston, MA}
}



@inproceedings{charikar2002similarity,
  title={Similarity estimation techniques from rounding algorithms},
  author={Charikar, Moses S},
  booktitle={Proceedings of the Thiry-Fourth Annual ACM Symposium on Theory of Computing (STOC)},
  pages={380--388},
  year={2002},
  address={Montreal, Canada}
}

@inproceedings{broder1997resemblance,
  title={On the resemblance and containment of documents},
  author={Broder, Andrei Z},
  booktitle={Proceedings of the Compression and Complexity of Sequences (SEQUENCES)},
  pages={21--29},
  year={1997},
  address={Salerno, Italy}
}


@inproceedings{wu2017consistent,
  title={Consistent weighted sampling made more practical},
  author={Wu, Wei and Li, Bin and Chen, Ling and Zhang, Chengqi},
  booktitle={Proceedings of the 26th International Conference on World Wide Web (WWW)},
  pages={1035--1043},
  year={2017},
  address={Perth, Australia}
}

@article{wu2018improved,
  title={Improved consistent weighted sampling revisited},
  author={Wu, Wei and Li, Bin and Chen, Ling and Zhang, Chengqi and Philip, S Yu},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  volume={31},
  number={12},
  pages={2332--2345},
  year={2018}
}

@inproceedings{li2007conditional,
  title={Conditional random sampling: A sketch-based sampling technique for sparse data},
  author={Li, Ping and Church, Kenneth W and Hastie, Trevor J},
  booktitle={Advances in Neural Information Processing Systems (NIPS)},
  pages={873--880},
  year={2007},
  address={Vancouver, Canada}
}


@inproceedings{qian2004similarity,
  title={Similarity between Euclidean and cosine angle distance for nearest neighbor queries},
  author={Qian, Gang and Sural, Shamik and Gu, Yuelong and Pramanik, Sakti},
  booktitle={Proceedings of the 2004 ACM Symposium on Applied Computing (SAC)},
  pages={1232--1237},
  year={2004},
  address={Nicosia, Cyprus}
}

@inproceedings{kokare2003comparison,
  title={Comparison of similarity metrics for texture image retrieval},
  author={Kokare, Manesh and Chatterji, BN and Biswas, PK},
  booktitle={Conference on Convergent Technologies for Asia-Pacific Region (TENCON)},
  volume={2},
  pages={571--575},
  year={2003},
  address={Bangalore, India}
}

@inproceedings{yu2006toward,
  title={Toward robust distance metric analysis for similarity estimation},
  author={Yu, Jie and Tian, Qi and Amores, Jaume and Sebe, Nicu},
  booktitle={IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
  volume={1},
  pages={316--322},
  year={2006},
  address={New York, NY}
}

@inproceedings{zheng2016lazylsh,
  title={Lazylsh: Approximate nearest neighbor search for multiple distance functions with a single index},
  author={Zheng, Yuxin and Guo, Qi and Tung, Anthony KH and Wu, Sai},
  booktitle={Proceedings of the 2016 SIGMOD International Conference on Management of Data (SIGMOD)},
  pages={2023--2037},
  year={2016},
  address={San Francisco, CA}
}

@article{wang2007improving,
  title={Improving nearest neighbor rule with a simple adaptive distance measure},
  author={Wang, Jigang and Neskovic, Predrag and Cooper, Leon N},
  journal={Pattern Recognition Letters},
  volume={28},
  number={2},
  pages={207--213},
  year={2007}
}

@inproceedings{tao2009quality,
  title={Quality and efficiency in high dimensional nearest neighbor search},
  author={Tao, Yufei and Yi, Ke and Sheng, Cheng and Kalnis, Panos},
  booktitle={Proceedings of the 2009 ACM SIGMOD International Conference on Management of data (SIGMOD)},
  pages={563--576},
  year={2009},
  address={Providence, RI}
}

@inproceedings{xinan2016an,
author = {Wang, Xinan and Dasgupta, Sanjoy},
title = {An Algorithm for l1 Nearest Neighbor Search via Monotonic Embedding},
year = {2016},
booktitle = {Proceedings of the 30th International Conference on Neural Information Processing Systems (NIPS)},
pages = {991–999},
address = {Barcelona, Spain}
}
  

@inproceedings{hamilton2020mosaic,
  author    = {Mark Hamilton and
               Stephanie Fu and
               Mindren Lu and
               Johnny Bui and
               Darius Bopp and
               Zhenbang Chen and
               Felix Tran and
               Margaret Wang and
               Marina Rogers and
               Lei Zhang and
               Chris Hoder and
               William T. Freeman},
  title     = {{MosAIc}: Finding Artistic Connections across Culture with Conditional
               Image Retrieval},
  booktitle = {Proceedings of NeurIPS 2020 Competition and Demonstration Track},
  address  = {Virtual Event / Vancouver,  Canada},
  pages     = {133--155},
  year      = {2020}
}
@inproceedings{davidson2010youtube,
  author    = {James Davidson and
               Benjamin Liebald and
               Junning Liu and
               Palash Nandy and
               Taylor Van Vleet and
               Ullas Gargi and
               Sujoy Gupta and
               Yu He and
               Mike Lambert and
               Blake Livingston and
               Dasarathi Sampath},
  title     = {The YouTube video recommendation system},
  booktitle = {Proceedings of the 2010 {ACM} Conference on Recommender Systems (RecSys)},
  address   = {Barcelona, Spain},
  pages     = {293--296},
  year      = {2010}
}


@inproceedings{kanakia2019scalable,
  author    = {Anshul Kanakia and
               Zhihong Shen and
               Darrin Eide and
               Kuansan Wang},
  title     = {A Scalable Hybrid Research Paper Recommender System for Microsoft
               Academic},
  booktitle = {Proceedings of the World Wide Web Conference (WWW)}, 
  address={San Francisco, CA},
  pages     = {2893--2899},
  year      = {2019}
}

@inproceedings{dror2011i,
  author    = {Gideon Dror and
               Yehuda Koren and
               Yoelle Maarek and
               Idan Szpektor},
  title     = {I want to answer; who has a question?: Yahoo! answers recommender
               system},
  booktitle = {Proceedings of the 17th {ACM} {SIGKDD} International Conference on
               Knowledge Discovery and Data Mining (KDD)},
  address={San Diego, CA},
  pages     = {1109--1117},
  year      = {2011}
}



@article{jain2010data,
  author    = {Anil K. Jain},
  title     = {Data clustering: 50 years beyond K-means},
  journal   = {Pattern Recognit. Lett.},
  volume    = {31},
  number    = {8},
  pages     = {651--666},
  year      = {2010}
}


@article{echihabi2021new,
author = {Echihabi, Karima and Zoumpatianos, Kostas and Palpanas, Themis},
title = {New Trends in High-D Vector Similarity Search: Al-Driven, Progressive, and Distributed},
year = {2021},
journal = {Proc. VLDB Endow.},
month = {jul},
pages = {3198–3201},
numpages = {4}
}

@article{xu2018online,
  author    = {Donna Xu and
               Ivor W. Tsang and
               Ying Zhang},
  title     = {Online Product Quantization},
  journal   = {{IEEE} Trans. Knowl. Data Eng.},
  volume    = {30},
  number    = {11},
  pages     = {2185--2198},
  year      = {2018}
}

@inproceedings{zhou2019mobius,
  author    = {Zhixin Zhou and
               Shulong Tan and
               Zhaozhuo Xu and
               Ping Li},
  title     = {M{\"{o}}bius Transformation for Fast Inner Product Search on
               Graph},
  booktitle = {Advances in Neural Information Processing Systems  (NeurIPS)},
  address   = {Vancouver, Canada},
  pages     = {8216--8227},
  year      = {2019}
}




@inproceedings{tan2021norm,
  author    = {Shulong Tan and
               Zhaozhuo Xu and
               Weijie Zhao and
               Hongliang Fei and
               Zhixin Zhou and
               Ping Li},
  title     = {Norm Adjusted Proximity Graph for Fast Inner Product Retrieval},
  booktitle = {Proceedings of the 27th {ACM} {SIGKDD} Conference on Knowledge Discovery
               and Data Mining (KDD)}, 
  address   = {Virtual Event, Singapore},
  pages     = {1552--1560},
  year      = {2021}
}

@article{xu2022proximity,
  title={Proximity Graph Maintenance for Fast Online Nearest Neighbor Search},
  author={Xu, Zhaozhuo and Zhao, Weijie and Tan, Shulong and Zhou, Zhixin and Li, Ping},
  journal={arXiv preprint arXiv:2206.10839},
  year={2022}
}

@inproceedings{zhu2018learning,
  author    = {Han Zhu and
               Xiang Li and
               Pengye Zhang and
               Guozheng Li and
               Jie He and
               Han Li and
               Kun Gai},
  title     = {Learning Tree-based Deep Model for Recommender Systems},
  booktitle = {Proceedings of the 24th {ACM} {SIGKDD} International Conference on
               Knowledge Discovery {\&} Data Mining (KDD)},
  address   = {London, UK},
  pages     = {1079--1088},
  year      = {2018}
}


@inproceedings{zhu2019joint,
  author    = {Han Zhu and
               Daqing Chang and
               Ziru Xu and
               Pengye Zhang and
               Xiang Li and
               Jie He and
               Han Li and
               Jian Xu and
               Kun Gai},
  title     = {Joint Optimization of Tree-based Index and Deep Model for Recommender
               Systems},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address  = {Vancouver, Canada},
  pages     = {3973--3982},
  year      = {2019}
}



@inproceedings{zhuo2020learning,
  author    = {Jingwei Zhuo and
               Ziru Xu and
               Wei Dai and
               Han Zhu and
               Han Li and
               Jian Xu and
               Kun Gai},
  title     = {Learning Optimal Tree Models under Beam Search},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {11650--11659},
  year      = {2020}
}
@article{gao2020deep,
  title={Deep Retrieval: Learning A Retrievable Structure for Large-Scale Recommendations},
  author={Gao, Weihao and Fan, Xiangjun and Wang, Chong and Sun, Jiankai and Jia, Kai and Xiao, Wenzhi and Ding, Ruofan and Bin, Xingyan and Yang, Hui and Liu, Xiaobing},
  journal={arXiv preprint arXiv:2007.07203},
  year={2020}
}

@inproceedings{yu2022egm,
  author    = {Tan Yu and
               Jie Liu and
               Yi Yang and
               Yi Li and
               Hongliang Fei and
               Ping Li},
  title     = {{EGM:} Enhanced Graph-based Model for Large-scale Video Advertisement
               Search},
  booktitle = {Proceedings of the 28th {ACM} {SIGKDD} Conference on Knowledge Discovery
               and Data Mining (KDD)}, 
  address   = {Washington, DC},
  pages     = {4443--4451},
  year      = {2022}
}



@inproceedings{li2021quantization,
  author    = {Xiaoyun Li and
               Ping Li},
  title     = {Quantization Algorithms for Random {Fourier} Features},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {6369--6380},
  year      = {2021}
}


@inproceedings{yang2018semantic,
  title={Semantic structure-based unsupervised deep hashing},
  author={Yang, Erkun and Deng, Cheng and Liu, Tongliang and Liu, Wei and Tao, Dacheng},
  booktitle={Proceedings of the 27th International Joint Conference on Artificial Intelligence},
  pages={1064--1070},
  year={2018}
}

@inproceedings{yang2019distillhash,
  author    = {Erkun Yang and
               Tongliang Liu and
               Cheng Deng and
               Wei Liu and
               Dacheng Tao},
  title     = {{DistillHash}: Unsupervised Deep Hashing by Distilling Data Pairs},
  booktitle = {Proceedings of the {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Long Beach, CA},
  pages     = {2946--2955},
  year      = {2019}
}


@inproceedings{dai2017stochastic,
  title={Stochastic generative hashing},
  author={Dai, Bo and Guo, Ruiqi and Kumar, Sanjiv and He, Niao and Song, Le},
  booktitle={Proceedings of the 34th International Conference on Machine Learning-Volume 70},
  pages={913--922},
  year={2017},
  organization={JMLR. org}
}

@inproceedings{cao2018hashgan,
  author    = {Yue Cao and
               Bin Liu and
               Mingsheng Long and
               Jianmin Wang},
  title     = {{HashGAN}: Deep Learning to Hash With Pair Conditional Wasserstein {GAN}},
  booktitle = {Proceedings of the 2018 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Salt Lake City, UT},
  pages     = {1287--1296},
  year      = {2018}
}


@inproceedings{ghasedi2018unsupervised,
  title={Unsupervised deep generative adversarial hashing network},
  author={Ghasedi Dizaji, Kamran and Zheng, Feng and Sadoughi, Najmeh and Yang, Yanhua and Deng, Cheng and Huang, Heng},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={3664--3673},
  year={2018}
}

@article{tolstikhin2017wasserstein,
  title={Wasserstein auto-encoders},
  author={Tolstikhin, Ilya and Bousquet, Olivier and Gelly, Sylvain and Schoelkopf, Bernhard},
  journal={arXiv preprint arXiv:1711.01558},
  year={2017}
}

@misc{iohara2019generative,
title={Generative model based on minimizing exact empirical Wasserstein distance},
author={Akihiro Iohara and Takahito Ogawa and Toshiyuki Tanaka},
year={2019},
url={https://openreview.net/forum?id=BJgTZ3C5FX},
}

@inproceedings{deshpande2019max,
  title={Max-Sliced Wasserstein Distance and its use for GANs},
  author={Deshpande, Ishan and Hu, Yuan-Ting and Sun, Ruoyu and Pyrros, Ayis and Siddiqui, Nasir and Koyejo, Sanmi and Zhao, Zhizhen and Forsyth, David and Schwing, Alexander G},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={10648--10656},
  year={2019}
}

@inproceedings{deshpande2018generative,
  title={Generative modeling using the Sliced Wasserstein Distance},
  author={Deshpande, Ishan and Zhang, Ziyu and Schwing, Alexander G},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={3483--3491},
  year={2018}
}

@article{bui2018sketching,
  title={Sketching out the details: Sketch-based image retrieval using convolutional neural networks with multi-stage regression},
  author={Bui, Tu and Ribeiro, Leonardo and Ponti, Moacir and Collomosse, John},
  journal={Computers \& Graphics},
  volume={71},
  pages={77--87},
  year={2018},
  publisher={Elsevier}
}

% AUTOENCODERS

@inproceedings{cho2014learning,
  title={Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation},
  author={Cho, Kyunghyun and van Merrienboer, Bart and Gulcehre, Caglar and Bahdanau, Dzmitry and Bougares, Fethi and Schwenk, Holger and Bengio, Yoshua},
  booktitle={Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  pages={1724--1734},
  year={2014}
}

@article{hill2016learning,
  title={Learning distributed representations of sentences from unlabelled data},
  author={Hill, Felix and Cho, Kyunghyun and Korhonen, Anna},
  journal={arXiv preprint arXiv:1602.03483},
  year={2016}
}

@inproceedings{bengio2013generalized,
  title={Generalized denoising auto-encoders as generative models},
  author={Bengio, Yoshua and Yao, Li and Alain, Guillaume and Vincent, Pascal},
  booktitle={Advances in Neural Information Processing Systems},
  pages={899--907},
  year={2013}
}

@article{salton1988term,
  title={Term-weighting approaches in automatic text retrieval},
  author={Salton, Gerard and Buckley, Christopher},
  journal={Information processing \& management},
  volume={24},
  number={5},
  pages={513--523},
  year={1988},
  publisher={Elsevier}
}

@article{deerwester1990indexing,
  title={Indexing by latent semantic analysis},
  author={Deerwester, Scott and Dumais, Susan T and Furnas, George W and Landauer, Thomas K and Harshman, Richard},
  journal={Journal of the American society for information science},
  volume={41},
  number={6},
  pages={391--407},
  year={1990},
  publisher={Wiley Online Library}
}


@article{zhang2015text,
  title={Text understanding from scratch},
  author={Zhang, Xiang and LeCun, Yann},
  journal={arXiv preprint arXiv:1502.01710},
  year={2015}
}

@inproceedings{zhang2015character,
  title={Character-level convolutional networks for text classification},
  author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},
  booktitle={Advances in neural information processing systems},
  pages={649--657},
  year={2015}
}

@inproceedings{liu2012supervised,
  author    = {Wei Liu and
               Jun Wang and
               Rongrong Ji and
               Yu{-}Gang Jiang and
               Shih{-}Fu Chang},
  title     = {Supervised hashing with kernels},
  booktitle = {Proceedings of the 2012 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Providence, RI},
  pages     = {2074--2081},
  year      = {2012}
}

@inproceedings{lin2016learning,
  author    = {Kevin Lin and
               Jiwen Lu and
               Chu{-}Song Chen and
               Jie Zhou},
  title     = {Learning Compact Binary Descriptors with Unsupervised Deep Neural
               Networks},
  booktitle = {Proceedings of the 2016 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Las Vegas, NV},
  pages     = {1183--1192},
  year      = {2016}
}

@inproceedings{ge2014graph,
  author    = {Tiezheng Ge and
               Kaiming He and
               Jian Sun},
  title     = {Graph Cuts for Supervised Binary Coding},
  booktitle = {Proceedings of the 13th European Conference on Computer Vision (ECCV), Part {VII}},
  address   = {Zurich,
               Switzerland},
  pages     = {250--264},
  year      = {2014}
}

@inproceedings{chaidaroon2017variational,
  title={Variational deep semantic hashing for text documents},
  author={Chaidaroon, Suthee and Fang, Yi},
  booktitle={Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  pages={75--84},
  year={2017},
  organization={ACM}
}

@inproceedings{shen2018nash,
  title={NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing},
  author={Shen, Dinghan and Su, Qinliang and Chapfuwa, Paidamoyo and Wang, Wenlin and Wang, Guoyin and Henao, Ricardo and Carin, Lawrence},
  booktitle={Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages={2041--2050},
  year={2018}
}

@inproceedings{heo2012spherical,
  title={Spherical hashing},
  author={Heo, Jae-Pil and Lee, Youngwoon and He, Junfeng and Chang, Shih-Fu and Yoon, Sung-Eui},
  booktitle={Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
  pages={2957--2964},
  year={2012},
  organization={IEEE}
}

@inproceedings{he2011compact,
  title={Compact hashing with joint optimization of search accuracy and time},
  author={He, Junfeng and Chang, Shih-Fu and Radhakrishnan, Regunathan and Bauer, Claus},
  booktitle={CVPR 2011},
  pages={753--760},
  year={2011},
  organization={IEEE}
}

@inproceedings{joly2011random,
  author    = {Alexis Joly and
               Olivier Buisson},
  title     = {Random maximum margin hashing},
  booktitle = {Proceedings of the 24th {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Colorado Springs, CO},
  pages     = {873--880},
  year      = {2011}
}


@article{lew2006content,
  title={Content-based multimedia information retrieval: State of the art and challenges},
  author={Lew, Michael S and Sebe, Nicu and Djeraba, Chabane and Jain, Ramesh},
  journal={ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)},
  volume={2},
  number={1},
  pages={1--19},
  year={2006},
  publisher={ACM}
}



@inproceedings{bawa2005lsh,
  title={LSH forest: self-tuning indexes for similarity search},
  author={Bawa, Mayank and Condie, Tyson and Ganesan, Prasanna},
  booktitle={Proceedings of the 14th international conference on World Wide Web},
  pages={651--660},
  year={2005},
  organization={ACM}
}

@inproceedings{schroder2011setting,
  title={Setting goals and choosing metrics for recommender system evaluations},
  author={Schr{\"o}der, Gunnar and Thiele, Maik and Lehner, Wolfgang},
  booktitle={UCERSTI2 Workshop at the 5th ACM Conference on Recommender Systems, Chicago, USA},
  volume={23},
  pages={53},
  year={2011}
}

@inproceedings{dong2008modeling,
  title={Modeling LSH for performance tuning},
  author={Dong, Wei and Wang, Zhe and Josephson, William and Charikar, Moses and Li, Kai},
  booktitle={Proceedings of the 17th ACM conference on Information and knowledge management},
  pages={669--678},
  year={2008},
  organization={ACM}
}

@article{slaney2012optimal,
  title={Optimal parameters for locality-sensitive hashing},
  author={Slaney, Malcolm and Lifshits, Yury and He, Junfeng},
  journal={Proceedings of the IEEE},
  volume={100},
  number={9},
  pages={2604--2623},
  year={2012},
  publisher={IEEE}
}


@article{wang2017survey,
  title={A survey on learning to hash},
  author={Wang, Jingdong and Zhang, Ting and Sebe, Nicu and Shen, Heng Tao and others},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  year={2017},
  publisher={IEEE}
}

@article{wang2014hashing,
  title={Hashing for similarity search: A survey},
  author={Wang, Jingdong and Shen, Heng Tao and Song, Jingkuan and Ji, Jianqiu},
  journal={arXiv preprint arXiv:1408.2927},
  year={2014}
}

@inproceedings{punjani2012fast,
  author    = {Mohammad Norouzi and
               Ali Punjani and
               David J. Fleet},
  title     = {Fast search in Hamming space with multi-index hashing},
  booktitle = {Proceedings of the 2012 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {
               Providence, RI},
  pages     = {3108--3115},
  year      = {2012}
}



@inproceedings{wang2013semantic,
  title={Semantic hashing using tags and topic modeling},
  author={Wang, Qifan and Zhang, Dan and Si, Luo},
  booktitle={Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval},
  pages={213--222},
  year={2013},
  organization={ACM}
}

@inproceedings{zhang2017deconvolutional,
  title={Deconvolutional paragraph representation learning},
  author={Zhang, Yizhe and Shen, Dinghan and Wang, Guoyin and Gan, Zhe and Henao, Ricardo and Carin, Lawrence},
  booktitle={Advances in Neural Information Processing Systems},
  pages={4169--4179},
  year={2017}
}

@article{kim2017adversarially,
  title={Adversarially regularized autoencoders for generating discrete structures},
  author={Kim, Yoon and Zhang, Kelly and Rush, Alexander M and LeCun, Yann and others},
  journal={arXiv preprint arXiv:1706.04223},
  year={2017}
}

@inproceedings{bowman2016generating,
  title={Generating Sentences from a Continuous Space},
  author={Bowman, Samuel R and Vilnis, Luke and Vinyals, Oriol and Dai, Andrew and Jozefowicz, Rafal and Bengio, Samy},
  booktitle={Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning},
  pages={10--21},
  year={2016}
}

@article{makhzani2015adversarial,
  title={Adversarial autoencoders},
  author={Makhzani, Alireza and Shlens, Jonathon and Jaitly, Navdeep and Goodfellow, Ian and Frey, Brendan},
  journal={arXiv preprint arXiv:1511.05644},
  year={2015}
}


@inproceedings{ma2016sub,
  title = {{A sub-linear massive-scale look-alike audience extension system}},
  author = {Ma, M and Wen, Z and Chen, Datong and others},
  booktitle = {Proceedings of the 5th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications},
  year = {2016},
}


@inproceedings{liu2016audience,
  title = {{Audience Expansion for Online Social Network Advertising}},
  author = {Liu, Haishan and Pardoe, David and Liu, Kun and Thakur, Manoj and Cao, Frank and Li, Chongzhe},
  booktitle = {Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  pages = {165--174},
  year = {2016},
  organization = {ACM},
}

@misc{qu2014systems,
  title={Systems and methods for generating expanded user segments},
  author={Qu, Yan and Wang, Jing and Sun, Yang and Holtan, Hans Marius},
  year={2014},
  month=feb # "~18",
  publisher={Google Patents},
  note={US Patent 8,655,695}
}

@book{leskovec2014mining,
  title={Mining of massive datasets},
  author={Leskovec, Jure and Rajaraman, Anand and Ullman, Jeffrey David},
  year={2014},
  publisher={Cambridge university press}
}

@inproceedings{shen2015effective,
  title = {{Effective audience extension in online advertising}},
  author = {Shen, Jianqiang and Geyik, Sahin Cem and Dasdan, Ali},
  booktitle = {Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  pages = {2099--2108},
  year = {2015},
  organization = {ACM},
}

@inproceedings{Liu2016,
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@BOOK{Book:FisherYates48,
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@book{Url:SinglePixel,
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@book{Url:Finite_Sample,
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@article{Article:Indyk2001,
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@Article{buher2001effcient,
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@Article{Article:Buher_03,
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  title         = "Provably Sensitive Indexing Strategies for
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@Article{Article:Buhler_JCB02,
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@Article{Article:Leung,
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@book{Book:NN_05,
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@book{Book:Cristianini_00,
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@book{Book:Gnedenko_54,
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@book{Book:Motwani,
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@book{Book:Vempala04,
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@inproceedings{Proc:Feinstein_DARPA03,
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@inproceedings{Proc:Zhao_IMC07,
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  booktitle     = "IMC",
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  year          = "2007"
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@article{Article:Broder_WWW97,
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@article{Article:GWAS_Nature07,
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@article{Article:Lee_Nature99,
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@inProceedings{Porc:Ruedin_04,
  author       = "Ana Ruedin and Javier Quinteros",
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@inproceedings{Proc:Goldstein_04,
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  booktitle = {Deterministic and Statistical Methods in Machine Learning},
  year      = {2004},
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@inproceedings{frund2007leanring,
  author    = {Yoav Freund and
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               Mayank Kabra and
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@article{Report:Chaudhuri_VLDB09,
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@article{Report:chandra_10,
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@inproceedings{Proc:Donoho_Curse_Notes,
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@inproceedings{Proc:Duffield_SIGCOM03,
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@inproceedings{Proc:Wang_Cloud04,
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  title     = {An Improved Cloud Classification Algorithm Based on the SGP CART Site Observations},
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@inproceedings{Proc:Duan_ISWC12,
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@inproceedings{Proc:Sahin_05,
  author    = {Ozgur D. Sahin and
               Aziz Gulbeden and
               Fatih Emek\c{c}i and
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  title     = {PRISM: indexing multi-dimensional data in P2P networks using
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  booktitle = {ACM Multimedia},
  year      = {2005},
  address   = {Singapore},
  pages     = {946-955}
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@inproceedings{bingham2001random,
  author    = {Ella Bingham and Heikki Mannila},
  title     = {Random projection in dimensionality reduction:
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@inproceedings{fern2003random,
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  year      = {2003},
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@inproceedings{Proc:Li_ICML09,
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  title     = {ABC-Boost: Adaptive Base Class Boost for Multi-Class Classification},
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  pages    = {625-632},
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@inproceedings{Proc:Li_UAI10,
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  title     = {Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost},
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@article{Article::Fisher_34,
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@article{Article:Dumais_Weighting,
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@article{achlioptas2003database,
  author    = {Dimitris Achlioptas},
  title     = {Database-friendly random projections: Johnson-Lindenstrauss with binary
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  journal   = {J. Comput. Syst. Sci.},
  volume    = {66},
  number    = {4},
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@article{Artilce:Kumar_JCSS04,
  author    = {Ziv Bar-Yossef and
               T. S. Jayram and
               Ravi Kumar and
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@article{Article:Donoho_PNAS09,
  title        = "Message-passing algorithms for compressed sensing",
  author        = "    David L. Donoho and    Arian Maleki and    Andrea Montanari",
  journal       = "PNAS",
  volume        = "106",
  number        = "45",
  year          = "2009",
  pages         = "18914-18919"
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@ARTICLE{Article:Gilbert_IEEE10,
author={Gilbert, Anna and Indyk, Piotr.},
journal={Proceedings of the IEEE},
title={Sparse Recovery Using Sparse Matrices},
year={2010},
month={june },
volume={98},
number={6},
pages={937 -947}
}

@techreport{Report:GraphKernel_arXiv14,
  author        = "Anshumali Shrivastava and Ping Li",
  title         = "Graph Kernels via Functional Embedding",
  institution       = "arXiv:1404.5214",
  year          = "2014"
}


@techreport{Report:Li_Zhang_L0,
  author        = "Ping Li and Cun-Hui Zhang",
  title         = "Exact Sparse Recovery with \text{L0} Projections",
  institution       = "arXiv:1302.0895",
  year          = "2013"
}

@techreport{Report:Li_CC_v0,
  author    = {Ping Li},
  title     = {On Approximating Frequency Moments of Data Streams with
               Skewed Projections},
  institution    = {arXiv:0802.0802,  	arXiv:1004.3782,   arXiv:0910.1403}
}
@techreport{Report:Li_FastABC,
  author        = "Ping Li",
  title         = "Fast ABC-Boost for Multi-Class Classification",
  institution       = "arXiv:1006.5051",
  year          = "2010"
}

@techreport{Report:RPCodeNonlinear2014,
  author        = "Ping Li and Michael Mitzenmacher and Anshumali Shrivastava",
  title         = "Coding for Random Projections and Nonlinear Estimators",
  year          = "2014"
}


@techreport{Report:CCCS,
  author        = "Ping Li and Cun-Hui Zhang and Tong Zhang",
  title         = "Compressed Counting Meets Compressed Sensing",
  year          = "2013",
  institution   = "arXiv:1310.1076"
}

@techreport{Report:VSCCCS,
  author        = "Ping Li and Cun-Hui Zhang and Tong Zhang",
  title         = "Sparse Recovery with Very Sparse Compressed Counting",
  year          = "2013"
}

@techreport{Report:Fuxin2013,
  author        = "Fuxin Li and Guy Lebanon and Cristian Sminchisescu",
  title         = "A Linear Approximation to the $\chi^2$ Kernel with Geometric Convergence",
  institution   = "arXiv:1206.4074",
  year          = "2013"
}

@article{Article:Amer-Yahia09,
 author = {Amer-Yahia, Sihem and Roy, Senjuti Basu and Chawlat, Ashish and Das, Gautam and Yu, Cong},
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 number = {1},
 year = {2009},
 pages = {754--765}
}

@inproceedings{li2016one,
  author        = "Ping Li",
  title         = "One Scan 1-bit Compressed Sensing",
  booktitle     = "Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS)",
  year          = "2016",
  pages         = "1515--1523",
  address       = "Cadiz, Spain"
}


@inproceedings{Proc:Chen_AISTATS15,
  author        = "Sheng Chen and Arindam Banerjee",
  title         = "One-bit Compressed Sensing with the k-Support Norm",
  booktitle     = "AISTATS",
  year          = "2015"
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@inproceedings{Proc:Zhu17-AHLFS,
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@inproceedings{Proc:Li18-UPFS,
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@inproceedings{Proc:Guo18-DGUFS,
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@Book{Book:Goodfellow2016,
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@inproceedings{Proc:Schlegl_IPMI17,
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@inproceedings{Proc:Brock_ICLR19,
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@inproceedings{Proc:Zhu_ICCV17,
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@techreport{arXiv:Ramesh_2018,
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@techreport{arXiv:Yang_2018,
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@techreport{arXiv:Arjovsky_2017,
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@inproceedings{Proc:Akcay_ACCV18,
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@inproceedings{Proc:Arvanitidis_ICLR18,
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@inproceedings{Proc:Dinh_ICLR17,
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               Matthias Minderer and
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@article{qi2017distributed,
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@inproceedings{huang2020causal,
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@article{yue2020interventional,
	title={Interventional few-shot learning},
	author={Yue, Zhongqi and Zhang, Hanwang and Sun, Qianru and Hua, Xian-Sheng},
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	volume={33},
	year={2020}
}

@article{hilliard2018few,
	title={Few-shot learning with metric-agnostic conditional embeddings},
	author={Hilliard, Nathan and Phillips, Lawrence and Howland, Scott and Yankov, Art{\"e}m and Corley, Courtney D and Hodas, Nathan O},
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	year={2018}
}

@inproceedings{li2020adversarial,
	title={Adversarial Feature Hallucination Networks for Few-Shot Learning},
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	year={2020}
}

@article{pan2010survey,
	title={A survey on transfer learning},
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@inproceedings{huang2006correcting,
	title={Correcting sample selection bias by unlabeled data},
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@inproceedings{azizpour2015generic,
	title={From generic to specific deep representations for visual recognition},
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	year={2015}
}

@article{long2015learning,
	title={Learning transferable features with deep adaptation networks},
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	year={2015}
}

@inproceedings{tzeng2015simultaneous,
	title={Simultaneous deep transfer across domains and tasks},
	author={Tzeng, Eric and Hoffman, Judy and Darrell, Trevor and Saenko, Kate},
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	year={2015}
}

@inproceedings{jha2020doubleu,
	title={Doubleu-net: A deep convolutional neural network for medical image segmentation},
	author={Jha, Debesh and Riegler, Michael A and Johansen, Dag and Halvorsen, P{\aa}l and Johansen, H{\aa}vard D},
	booktitle={2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)},
	pages={558--564},
	year={2020},
	organization={IEEE}
}

@article{tao2020hierarchical,
	title={Hierarchical multi-scale attention for semantic segmentation},
	author={Tao, Andrew and Sapra, Karan and Catanzaro, Bryan},
	journal={arXiv preprint arXiv:2005.10821},
	year={2020}
}

@inproceedings{fu2019dual,
	title={Dual attention network for scene segmentation},
	author={Fu, Jun and Liu, Jing and Tian, Haijie and Li, Yong and Bao, Yongjun and Fang, Zhiwei and Lu, Hanqing},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={3146--3154},
	year={2019}
}

@article{duan2012visual,
	title={Visual event recognition in videos by learning from web data},
	author={Duan, Lixin and Xu, Dong and Tsang, Ivor Wai-Hung and Luo, Jiebo},
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@InProceedings{Lin_2017_CVPR,
author = {Lin, Tsung-Yi and Dollar, Piotr and Girshick, Ross and He, Kaiming and Hariharan, Bharath and Belongie, Serge},
title = {Feature Pyramid Networks for Object Detection},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}

@inproceedings{zhang2018context,
  title={Context encoding for semantic segmentation},
  author={Zhang, Hang and Dana, Kristin and Shi, Jianping and Zhang, Zhongyue and Wang, Xiaogang and Tyagi, Ambrish and Agrawal, Amit},
  booktitle={Proceedings of the IEEE conference on Computer Vision and Pattern Recognition},
  pages={7151--7160},
  year={2018}
}

@inproceedings{hu2018squeeze,
  title={Squeeze-and-excitation networks},
  author={Hu, Jie and Shen, Li and Sun, Gang},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={7132--7141},
  year={2018}
}

@inproceedings{fu2019dual,
  title={Dual attention network for scene segmentation},
  author={Fu, Jun and Liu, Jing and Tian, Haijie and Li, Yong and Bao, Yongjun and Fang, Zhiwei and Lu, Hanqing},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={3146--3154},
  year={2019}
}

@inproceedings{lin2014microsoft,
  author    = {Tsung{-}Yi Lin and
               Michael Maire and
               Serge J. Belongie and
               James Hays and
               Pietro Perona and
               Deva Ramanan and
               Piotr Doll{\'{a}}r and
               C. Lawrence Zitnick},
  title     = {Microsoft {COCO:} Common Objects in Context},
  booktitle = {Computer Vision - {ECCV} 2014 - Proceedings of the 13th European Conference on Computer Vision (ECCV), Part {V}}, 
  address   = {Zurich,
               Switzerland},
  pages     = {740--755},
  year      = {2014}
}

@inproceedings{wang2018non,
  author    = {Xiaolong Wang and
               Ross B. Girshick and
               Abhinav Gupta and
               Kaiming He},
  title     = {Non-Local Neural Networks},
  booktitle = {Proceedings of the 2018 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Salt Lake City, UT},
  pages     = {7794--7803},
  year      = {2018}
}

@inproceedings{bello2019attention,
  author    = {Irwan Bello and
               Barret Zoph and
               Quoc Le and
               Ashish Vaswani and
               Jonathon Shlens},
  title     = {Attention Augmented Convolutional Networks},
  booktitle = {Proceedings of the 2019 {IEEE/CVF} International Conference on Computer Vision (ICCV)}, 
  address   = {Seoul, Korea},
  pages     = {3285--3294},
  year      = {2019}
}

@inproceedings{peng2017large,
  title={Large kernel matters--improve semantic segmentation by global convolutional network},
  author={Peng, Chao and Zhang, Xiangyu and Yu, Gang and Luo, Guiming and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={4353--4361},
  year={2017}
}
@inproceedings{cordts2016cityscapes,
  title={The cityscapes dataset for semantic urban scene understanding},
  author={Cordts, Marius and Omran, Mohamed and Ramos, Sebastian and Rehfeld, Timo and Enzweiler, Markus and Benenson, Rodrigo and Franke, Uwe and Roth, Stefan and Schiele, Bernt},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={3213--3223},
  year={2016}
}

@inproceedings{parmar2018image,
  author    = {Niki Parmar and
               Ashish Vaswani and
               Jakob Uszkoreit and
               Lukasz Kaiser and
               Noam Shazeer and
               Alexander Ku and
               Dustin Tran},
  title     = {Image Transformer},
  booktitle = {Proceedings of the 35th International Conference on Machine Learning (ICML)},
  address   = {Stockholmsm{\"{a}}ssan, Stockholm, Sweden},
  pages     = {4052--4061},
  year      = {2018}
}

@inproceedings{qiu2020blockwise,
  author    = {Jiezhong Qiu and
               Hao Ma and
               Omer Levy and
               Wen{-}tau Yih and
               Sinong Wang and
               Jie Tang},
  title     = {Blockwise Self-Attention for Long Document Understanding},
  booktitle = {Findings of the Association for Computational Linguistics (EMNLP Findings)},
  address   = {Online Event},
  pages     = {2555--2565},
  year      = {2020}
}


@article{child2019generating,
  title={Generating long sequences with sparse transformers},
  author={Child, Rewon and Gray, Scott and Radford, Alec and Sutskever, Ilya},
  journal={arXiv preprint arXiv:1904.10509},
  year={2019}
}


@article{beltagy2020longformer,
  title={Longformer: The long-document transformer},
  author={Beltagy, Iz and Peters, Matthew E and Cohan, Arman},
  journal={arXiv preprint arXiv:2004.05150},
  year={2020}
}


@inproceedings{touvron2021training,
  author    = {Hugo Touvron and
               Matthieu Cord and
               Matthijs Douze and
               Francisco Massa and
               Alexandre Sablayrolles and
               Herv{\'{e}} J{\'{e}}gou},
  title     = {Training data-efficient image transformers {\&} distillation through
               attention},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {10347--10357},
  year      = {2021}
}

@article{tay2020efficient,
  title={Efficient transformers: A survey},
  author={Tay, Yi and Dehghani, Mostafa and Bahri, Dara and Metzler, Donald},
  journal={arXiv preprint arXiv:2009.06732},
  year={2020}
}

@inproceedings{tay2020sparse,
  author    = {Yi Tay and
               Dara Bahri and
               Liu Yang and
               Donald Metzler and
               Da{-}Cheng Juan},
  title     = {Sparse Sinkhorn Attention},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {9438--9447},
  year      = {2020}
}

@InProceedings{yuan2021tokens,
  author    = {Li Yuan and
               Yunpeng Chen and
               Tao Wang and
               Weihao Yu and
               Yujun Shi and
               Zihang Jiang and
               Francis E. H. Tay and
               Jiashi Feng and
               Shuicheng Yan},
  title     = {{Tokens-to-Token ViT}: Training Vision Transformers from Scratch on
               {ImageNet}},
  booktitle = {Proceedings of the 2021 {IEEE/CVF} International Conference on Computer Vision (ICCV)},
  address   = {Montreal, Canada},
  pages     = {538--547},
  year      = {2021}
}

@inproceedings{han2021transformer,
  author    = {Kai Han and
               An Xiao and
               Enhua Wu and
               Jianyuan Guo and
               Chunjing Xu and
               Yunhe Wang},
  title     = {Transformer in Transformer},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {virtual},
  pages     = {15908--15919},
  year      = {2021}
}

@inproceedings{liu2021swin,
  author    = {Ze Liu and
               Yutong Lin and
               Yue Cao and
               Han Hu and
               Yixuan Wei and
               Zheng Zhang and
               Stephen Lin and
               Baining Guo},
  title     = {Swin Transformer: Hierarchical Vision Transformer using Shifted Windows},
  booktitle = {Proceedings of the 2021 {IEEE/CVF} International Conference on Computer Vision (ICCV)},
  address   = {Montreal, Canada},
  pages     = {9992--10002},
  year      = {2021}
}



@inproceedings{chu2021twins,
  author    = {Xiangxiang Chu and
               Zhi Tian and
               Yuqing Wang and
               Bo Zhang and
               Haibing Ren and
               Xiaolin Wei and
               Huaxia Xia and
               Chunhua Shen},
  title     = {Twins: Revisiting the Design of Spatial Attention in Vision Transformers},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {virtual},
  pages     = {9355--9366},
  year      = {2021}
}



@article{roy2021efficient,
  author    = {Aurko Roy and
               Mohammad Saffar and
               Ashish Vaswani and
               David Grangier},
  title     = {Efficient Content-Based Sparse Attention with Routing Transformers},
  journal   = {Trans. Assoc. Comput. Linguistics},
  volume    = {9},
  pages     = {53--68},
  year      = {2021}
}

@inproceedings{kitaev2020reformer,
  author    = {Nikita Kitaev and
               Lukasz Kaiser and
               Anselm Levskaya},
  title     = {Reformer: The Efficient Transformer},
  booktitle = {Proceedings of the 8th International Conference on Learning Representations (ICLR)},
  address   = {
               Addis Ababa, Ethiopia},
  year      = {2020}
}


@article{andoni2015practical,
  title={Practical and optimal LSH for angular distance},
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@inproceedings{radosavovic2020designing,
  author    = {Ilija Radosavovic and
               Raj Prateek Kosaraju and
               Ross B. Girshick and
               Kaiming He and
               Piotr Doll{\'{a}}r},
  title     = {Designing Network Design Spaces},
  booktitle = {Proceedings of the 2020 {IEEE/CVF} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Seattle, WA},
  pages     = {10425--10433},
  year      = {2020}
}

@inproceedings{dong2022cswin,
  author    = {Xiaoyi Dong and
               Jianmin Bao and
               Dongdong Chen and
               Weiming Zhang and
               Nenghai Yu and
               Lu Yuan and
               Dong Chen and
               Baining Guo},
  title     = {{CSWin} Transformer: {A} General Vision Transformer Backbone with Cross-Shaped
               Windows},
  booktitle = {Proceedings of the {IEEE/CVF} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {New Orleans, LA},
  pages     = {12114--12124},
  year      = {2022}
}

@inproceedings{wang2021pyramid,
  author    = {Wenhai Wang and
               Enze Xie and
               Xiang Li and
               Deng{-}Ping Fan and
               Kaitao Song and
               Ding Liang and
               Tong Lu and
               Ping Luo and
               Ling Shao},
  title     = {Pyramid Vision Transformer: {A} Versatile Backbone for Dense Prediction
               without Convolutions},
  booktitle = {Proceedings of the 2021 {IEEE/CVF} International Conference on Computer Vision (ICCV)},
  address   = {Montreal,  Canada},
  pages     = {548--558},
  year      = {2021}
}


@InProceedings{heo2021rethinking,
  author    = {Byeongho Heo and
               Sangdoo Yun and
               Dongyoon Han and
               Sanghyuk Chun and
               Junsuk Choe and
               Seong Joon Oh},
  title     = {Rethinking Spatial Dimensions of Vision Transformers},
  booktitle = {Proceedings of the 2021 {IEEE/CVF} International Conference on Computer Vision (ICCV)},
  address   = {Montreal, Canada},
  pages     = {11916--11925},
  year      = {2021}
}


@article{strudel2021segmenter,
  title={Segmenter: Transformer for Semantic Segmentation},
  author={Strudel, Robin and Garcia, Ricardo and Laptev, Ivan and Schmid, Cordelia},
  journal={arXiv preprint arXiv:2105.05633},
  year={2021}
}

@inproceedings{yang2021focal,
  author    = {Jianwei Yang and
               Chunyuan Li and
               Pengchuan Zhang and
               Xiyang Dai and
               Bin Xiao and
               Lu Yuan and
               Jianfeng Gao},
  title     = {Focal Attention for Long-Range Interactions in Vision Transformers},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {virtual},
  pages     = {30008--30022},
  year      = {2021}
}

@article{wang2021pvtv2,
  title={{PVTv2}: Improved Baselines with Pyramid Vision Transformer},
  author={Wang, Wenhai and Xie, Enze and Li, Xiang and Fan, Deng-Ping and Song, Kaitao and Liang, Ding and Lu, Tong and Luo, Ping and Shao, Ling},
  journal={arXiv preprint arXiv:2106.13797},
  year={2021}
}


@InProceedings{zhou2017scene,
  author    = {Bolei Zhou and
               Hang Zhao and
               Xavier Puig and
               Sanja Fidler and
               Adela Barriuso and
               Antonio Torralba},
  title     = {Scene Parsing through {ADE20K} Dataset},
  booktitle = {Proceedings of the 2017 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Honolulu, HI},
  pages     = {5122--5130},
  year      = {2017}
}



@inproceedings{zhang2022nested,
  author    = {Zizhao Zhang and
               Han Zhang and
               Long Zhao and
               Ting Chen and
               Sercan {\"{O}}. Arik and
               Tomas Pfister},
  title     = {Nested Hierarchical Transformer: Towards Accurate, Data-Efficient
               and Interpretable Visual Understanding},
  booktitle = {Proceedings of the thirty-Sixth {AAAI} Conference on Artificial Intelligence (AAAI)},
  address   = {Virtual Event},
  pages     = {3417--3425},
  year      = {2022}
}

@inproceedings{yu2021rethinking,
  author    = {Tan Yu and
               Xu Li and
               Yunfeng Cai and
               Mingming Sun and
               Ping Li},
  title     = {Rethinking Token-Mixing {MLP} for {MLP}-based Vision Backbone},
  booktitle = {Proceedings of the 32nd British Machine Vision Conference (BMVC)},
  address   = {Online},
  pages     = {139},
  year      = {2021}
}

@inproceedings{yu2022s2mlp,
  author    = {Tan Yu and
               Xu Li and
               Yunfeng Cai and
               Mingming Sun and
               Ping Li},
  title     = {{S\({}^{\mbox{2}}\)-MLP}: Spatial-Shift {MLP} Architecture for Vision},
  booktitle = {Proceedings of the {IEEE/CVF} Winter Conference on Applications of Computer Vision (WACV)},
  address   = {Waikoloa, HI},
  pages     = {3615--3624},
  year      = {2022}
}


@article{yu2021s2mlpv2,
  title={{S$^{2}$-MLPv2}: Improved Spatial-Shift MLP Architecture for Vision},
  author={Yu, Tan and Li, Xu and Cai, Yunfeng and Sun, Mingming and Li, Ping},
  journal={arXiv preprint arXiv:2108.01072},
  year={2021}
}


@article{chen2022r2mlp,
  title={{R$^2$-MLP}: Round-Roll {MLP} Architecture for Multi-View {3D} Object Recognition},
  author={Shuo Chen and Tan Yu and Ping Li},
  journal={preprint},
  year={2022}
}

@article{yu2022degenerate,
  title={Degenerate {Swin} to {Win}: Plain Window-based Transformer without Sophisticated Operations},
  author={Yu, Tan and Li, Ping},
  journal={arXiv preprint arXiv:2211.14255},
  year={2022}
}

@article{esteva2017dermatologist,
  title={Dermatologist-level classification of skin cancer with deep neural networks},
  author={Esteva, Andre and Kuprel, Brett and Novoa, Roberto A and Ko, Justin and Swetter, Susan M and Blau, Helen M and Thrun, Sebastian},
  journal={Nature},
  volume={542},
  number={7639},
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  publisher={Nature Publishing Group}
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@inproceedings{choi2016doctor,
  title={Doctor ai: Predicting clinical events via recurrent neural networks},
  author={Choi, Edward and Bahadori, Mohammad Taha and Schuetz, Andy and Stewart, Walter F and Sun, Jimeng},
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  pages={301--318},
  year={2016}
}

@inproceedings{saxe2015deep,
  title={Deep neural network based malware detection using two dimensional binary program features},
  author={Saxe, Joshua and Berlin, Konstantin},
  booktitle={10th International Conference on Malicious and Unwanted Software ({MALWARE})},
  pages={11--20},
  year={2015},
  organization={IEEE}
}

@article{chandra2015web,
  title={Web spam classification using supervised artificial neural network algorithms},
  author={Chandra, Ashish and Suaib, Mohammad and Beg, Rizwan},
  journal={Advanced Computational Intelligence: An International Journal ({ACII})},
  year={2015}
}

@inproceedings{parkhi2015deep,
  title={Deep Face Recognition},
  author={Parkhi, Omkar M and Vedaldi, Andrea and Zisserman, Andrew},
  booktitle={BMVC},
  volume={1},
  number={3},
  pages={6},
  year={2015}
}
@inproceedings{sun2014deep,
  title={Deep learning face representation from predicting 10,000 classes},
  author={Sun, Yi and Wang, Xiaogang and Tang, Xiaoou},
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  year={2014}
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@article{karu1996fingerprint,
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%%%%%autonomous driving
@inproceedings{chen2015deepdriving,
  title={Deepdriving: Learning affordance for direct perception in autonomous driving},
  author={Chen, Chenyi and Seff, Ari and Kornhauser, Alain and Xiao, Jianxiong},
  booktitle={IEEE International Conference on Computer Vision ({ICCV})},
  pages={2722--2730},
  year={2015},
  organization={IEEE}
}
%%%%%stock prediction
@article{moghaddam2016stock,
  title={Stock market index prediction using artificial neural network},
  author={Moghaddam, Amin Hedayati and Moghaddam, Moein Hedayati and Esfandyari, Morteza},
  journal={Journal of Economics, Finance and Administrative Science},
  volume={21},
  number={41},
  pages={89--93},
  year={2016},
  publisher={Elsevier}
}
%%%%Data mining
@book{witten2016data,
  title={Data Mining: Practical machine learning tools and techniques},
  author={Witten, Ian H and Frank, Eibe and Hall, Mark A and Pal, Christopher J},
  year={2016},
  publisher={Morgan Kaufmann}
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@article{tehranipoor2010survey,
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  publisher={IEEE}
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@inproceedings{wei2012hardware,
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  organization={ACM}
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@inproceedings{chakraborty2009hardware,
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  organization={IEEE}
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@inproceedings{jin2008hardware,
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  year={2008}
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@inproceedings{chakraborty2009security,
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@article{bhunia2013protection,
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@article{xiao2016hardware,
  author    = {Kan Xiao and
               Domenic Forte and
               Yier Jin and
               Ramesh Karri and
               Swarup Bhunia and
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  title     = {Hardware Trojans: Lessons Learned after One Decade of Research},
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@inproceedings{ghandali2016design,
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  year={2016}
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@article{narasimhan2013hardware,
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@inproceedings{xiao2015efficient,
  title={Efficient and secure split manufacturing via obfuscated built-in self-authentication},
  author={Xiao, Kan and Forte, Domenic and Tehranipoor, Mark Mohammed},
  booktitle={{IEEE} International Symposium on Hardware Oriented Security and Trust ({HOST})},
  pages={14--19},
  year={2015}
}


@article{moosavi2017universal,
  title={Universal adversarial perturbations},
  author={Moosavi-Dezfooli, Seyed-Mohsen and Fawzi, Alhussein and Fawzi, Omar and Frossard, Pascal},
  journal={{IEEE} Conference on Computer Vision and Pattern Recognition ({CVPR})},
  year={2017}
}
%%%%%survey
@article{akhtar2018threat,
  title={Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey},
  author={Akhtar, Naveed and Mian, Ajmal},
  journal={{IEEE} Access},
  volume={6},
  pages={14410--14430},
  year={2018},
  publisher={IEEE}
}
%%%%%SM
@article{su2017one,
  title={One pixel attack for fooling deep neural networks},
  author={Su, Jiawei and Vargas, Danilo Vasconcellos and Kouichi, Sakurai},
  journal={arXiv preprint arXiv:1710.08864},
  year={2017}
}
%%%%%LBFS
@inproceedings{szegedy2013intriguing,
  author    = {Christian Szegedy and
               Wojciech Zaremba and
               Ilya Sutskever and
               Joan Bruna and
               Dumitru Erhan and
               Ian J. Goodfellow and
               Rob Fergus},
  title     = {Intriguing properties of neural networks},
  booktitle = {Proceedings of the 2nd International Conference on Learning Representations (ICLR)},
  address   = {Banff, Canada},
  year      = {2014}
}


%%%%spatial
@article{xiao2018spatially,
  title={Spatially transformed adversarial examples},
  author={Xiao, Chaowei and Zhu, Jun-Yan and Li, Bo and He, Warren and Liu, Mingyan and Song, Dawn},
  journal={International Conference on Learning Representations ({ICLR})},
  year={2018}
}
%%%%C&W
@inproceedings{carlini2017towards,
  title={Towards evaluating the robustness of neural networks},
  author={Carlini, Nicholas and Wagner, David},
  booktitle={{IEEE} Symposium on Security and Privacy ({SP})},
  pages={39--57},
  year={2017},
  organization={IEEE}
}

@article{yuan2017adversarial,
  title={Adversarial Examples: Attacks and Defenses for Deep Learning},
  author={Yuan, Xiaoyong and He, Pan and Zhu, Qile and Bhat, Rajendra Rana and Li, Xiaolin},
  journal={arXiv preprint arXiv:1712.07107},
  year={2017}
}

@article{sabour2015adversarial,
  title={Adversarial manipulation of deep representations},
  author={Sabour, Sara and Cao, Yanshuai and Faghri, Fartash and Fleet, David J},
  journal={International Conference on Learning Representations ({ICLR})},
  year={2016}
}
@inproceedings{papernot2016limitations,
  author    = {Nicolas Papernot and
               Patrick D. McDaniel and
               Somesh Jha and
               Matt Fredrikson and
               Z. Berkay Celik and
               Ananthram Swami},
  title     = {The Limitations of Deep Learning in Adversarial Settings},
  booktitle = {Proceedings of the {IEEE} European Symposium on Security and Privacy (EuroS{\&}P)},
  address   = {Saarbr{\"{u}}cken, Germany},
  pages     = {372--387},
  year      = {2016}
}

@inproceedings{goodfellow2014explaining,
  author    = {Ian J. Goodfellow and
               Jonathon Shlens and
               Christian Szegedy},
  title     = {Explaining and Harnessing Adversarial Examples},
  booktitle = {Proceedings of the 3rd International Conference on Learning Representations (ICLR)},
  address   = {San Diego, CA},
  year      = {2015}
}

@article{sinha2017certifiable,
  title={Certifiable Some Distributional Robustness with Principled Adversarial Training},
  author={Sinha, Aman and Namkoong, Hongseok and Duchi, John},
  journal={International Conference on Learning Representations ({ICLR})},
  year={2017}
}
@article{abbasi2017robustness,
  title={Robustness to adversarial examples through an ensemble of specialists},
  author={Abbasi, Mahdieh and Gagn{\'e}, Christian},
  journal={5th International Conference on Learning Representations ({ICLR}) Workshop},
  year={2017}
}

@inproceedings{papernot2016crafting,
  title={Crafting adversarial input sequences for recurrent neural networks},
  author={Papernot, Nicolas and McDaniel, Patrick and Swami, Ananthram and Harang, Richard},
  booktitle={{IEEE} Military Communications Conference},
  pages={49--54},
  year={2016}
}

%AE Defences
@article{tramer2017ensemble,
  title={Ensemble adversarial training: Attacks and defenses},
  author={Tram{\`e}r, Florian and Kurakin, Alexey and Papernot, Nicolas and Boneh, Dan and McDaniel, Patrick},
  journal={International Conference on Learning Representations ({ICLR})},
  year={2018}
}

%NN software trojans%
@inproceedings{liu2017neural,
  author    = {Yuntao Liu and
               Yang Xie and
               Ankur Srivastava},
  title     = {Neural Trojans},
  booktitle = {Proceedings of the 2017 {IEEE} International Conference on Computer Design (ICCD)},
  address   = {
               Boston, MA},
  pages     = {45--48},
  year      = {2017}
}


@inproceedings{liu2017trojaning,
  author    = {Yingqi Liu and
               Shiqing Ma and
               Yousra Aafer and
               Wen{-}Chuan Lee and
               Juan Zhai and
               Weihang Wang and
               Xiangyu Zhang},
  title     = {Trojaning Attack on Neural Networks},
  booktitle = {Proceedings of the 25th Annual Network and Distributed System Security Symposium (NDSS)},
  address   = {San Diego, CA},
  year      = {2018}
}


@article{geigel2013neural,
  title={Neural network Trojan},
  author={Geigel, Arturo},
  journal={Journal of Computer Security},
  volume={21},
  number={2},
  pages={191--232},
  year={2013}
}

%NN hardware security%
@inproceedings{liu2017fault,
  title={Fault injection attack on deep neural network},
  author={Liu, Yannan and Wei, Lingxiao and Luo, Bo and Xu, Qiang},
  booktitle={{IEEE}/{ACM} International Conference on Computer-Aided Design ({ICCAD})},
  pages={131--138},
  year={2017},
  organization={IEEE}
}

@inproceedings{chen2014dadiannao,
  title={Dadiannao: A machine-learning supercomputer},
  author={Chen, Yunji and Luo, Tao and Liu, Shaoli and Zhang, Shijin and He, Liqiang and Wang, Jia and Li, Ling and Chen, Tianshi and Xu, Zhiwei and Sun, Ninghui and Teman, Olivier},
  booktitle={Proceedings of the 47th Annual {IEEE}/{ACM} International Symposium on Microarchitecture},
  pages={609--622},
  year={2014}
}

%Adversarial ML%
@article{frederickson2018attack,
  title={Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning},
  author={Frederickson, Christopher and Moore, Michael and Dawson, Glenn and Polikar, Robi},
  journal={arXiv preprint arXiv:1802.07295},
  year={2018}
}
@article{papernot2016towards,
  title={Towards the science of security and privacy in machine learning},
  author={Papernot, Nicolas and McDaniel, Patrick and Sinha, Arunesh and Wellman, Michael},
  journal={{IEEE} European Symposium on Security and Privacy},
  year={2016}
}
@inproceedings{hein2017formal,
  title={Formal guarantees on the robustness of a classifier against adversarial manipulation},
  author={Hein, Matthias and Andriushchenko, Maksym},
  booktitle={Advances in Neural Information Processing Systems},
  pages={2263--2273},
  year={2017}
}
@article{chen2017targeted,
  title={Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning},
  author={Chen, Xinyun and Liu, Chang and Li, Bo and Lu, Kimberly and Song, Dawn},
  journal={arXiv preprint arXiv:1712.05526},
  year={2017}
}
@inproceedings{barreno2006can,
  title={Can machine learning be secure?},
  author={Barreno, Marco and Nelson, Blaine and Sears, Russell and Joseph, Anthony D and Tygar, J Doug},
  booktitle={Proceedings of the {ACM} Symposium on Information, computer and communications security},
  pages={16--25},
  year={2006}
}
@article{mozaffari2015systematic,
  title={Systematic poisoning attacks on and defenses for machine learning in healthcare},
  author={Mozaffari-Kermani, Mehran and Sur-Kolay, Susmita and Raghunathan, Anand and Jha, Niraj K},
  journal={{IEEE} journal of biomedical and health informatics},
  volume={19},
  number={6},
  pages={1893--1905},
  year={2015}
}

@article{clements2018hardware,
  title={Hardware Trojan Attacks on Neural Networks},
  author={Clements, Joseph and Lao, Yingjie},
  journal={arXiv preprint arXiv:1806.05768},
  year={2018}
}

@inproceedings{krizhevsky2012imagenet,
  author    = {Alex Krizhevsky and
               Ilya Sutskever and
               Geoffrey E. Hinton},
  title     = {{ImageNet} Classification with Deep Convolutional Neural Networks},
  booktitle = {Advances in Neural Information Processing Systems (NIPS)},
  address   = {Lake Tahoe, NV},
  pages     = {1106--1114},
  year      = {2012}
}

@article{barreno2010security,
	title={The security of machine learning},
	author={Barreno, Marco and Nelson, Blaine and Joseph, Anthony D and Tygar, JD},
	journal={Machine Learning},
	volume={81},
	number={2},
	pages={121--148},
	year={2010},
	publisher={Springer}
}

@article{biggio2012poisoning,
	title={Poisoning attacks against support vector machines},
	author={Biggio, Battista and Nelson, Blaine and Laskov, Pavel},
	journal={International Conference on Machine Learning ({ICML})},
	year={2012}
}

@inproceedings{xiao2012adversarial,
	title={Adversarial Label Flips Attack on Support Vector Machines.},
	author={Xiao, Han and Xiao, Huang and Eckert, Claudia},
	booktitle={ECAI},
	pages={870--875},
	year={2012}
}

@article{yang2017generative,
	title={Generative poisoning attack method against neural networks},
	author={Yang, Chaofei and Wu, Qing and Li, Hai and Chen, Yiran},
	journal={arXiv preprint arXiv:1703.01340},
	year={2017}
}

@article{sarwar2017incremental,
	title={Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing},
	author={Sarwar, Syed Shakib and Ankit, Aayush and Roy, Kaushik},
	journal={arXiv preprint arXiv:1712.02719},
	year={2017}
}

@article{ratcliff1990connectionist,
	title={Connectionist models of recognition memory: constraints imposed by learning and forgetting functions.},
	author={Ratcliff, Roger},
	journal={Psychological review},
	volume={97},
	number={2},
	pages={285},
	year={1990},
	publisher={{US}: American Psychological Association}
}

@inproceedings{shmelkov2017incremental,
  title={Incremental Learning of Object Detectors without Catastrophic Forgetting},
  author={Shmelkov, Konstantin and Schmid, Cordelia and Alahari, Karteek},
  booktitle={{IEEE} International Conference on Computer Vision ({ICCV})},
  pages={3420--3429},
  year={2017},
  organization={IEEE}
}



@inproceedings{papernot2015distillation,
  title={Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks},
  author={Papernot, Nicolas and McDaniel, Patrick and Wu, Xi and Jha, Somesh and Swami, Ananthram},
  booktitle={{IEEE} Symposium on Security and Privacy ({SP})},
  year={2015},
  organization={Institute of Electrical and Electronics Engineers Inc.}
}


@inproceedings{han2015learning,
	title={Learning both weights and connections for efficient neural network},
	author={Han, Song and Pool, Jeff and Tran, John and Dally, William},
	booktitle={Advances in neural information processing systems},
	pages={1135--1143},
	year={2015}
}

@article{ye2018defending,
	title={Defending {DNN} Adversarial Attacks with Pruning and Logits Augmentation},
	author={Ye, Shaokai and Wang, Siyue and Wang, Xiao and Yuan, Bo and Wen, Wujie and Lin, Xue},
	year={2018}
}

@inproceedings{liu2018fine,
  author    = {Kang Liu and
               Brendan Dolan{-}Gavitt and
               Siddharth Garg},
  title     = {Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural
               Networks},
  booktitle = {Proceedings of the 21st International
               Symposium on Research in Attacks, Intrusions, and Defenses (RAID)},
  address   = {Heraklion, Crete, Greece},
  pages     = {273--294},
  year      = {2018}
}

@inproceedings{carlini2017adversarial,
  author    = {Nicholas Carlini and
               David A. Wagner},
  editor    = {Bhavani M. Thuraisingham and
               Battista Biggio and
               David Mandell Freeman and
               Brad Miller and
               Arunesh Sinha},
  title     = {Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection
               Methods},
  booktitle = {Proceedings of the 10th {ACM} Workshop on Artificial Intelligence
               and Security (AISec@CCS)},
  address   = {Dallas, TX},
  pages     = {3--14},
  year      = {2017}
}


@article{bhagoji2017dimensionality,
	title={Dimensionality reduction as a defense against evasion attacks on machine learning classifiers},
	author={Bhagoji, Arjun Nitin and Cullina, Daniel and Mittal, Prateek},
	journal={arXiv preprint},
	year={2017}
}

@article{feinman2017detecting,
	title={Detecting adversarial samples from artifacts},
	author={Feinman, Reuben and Curtin, Ryan R and Shintre, Saurabh and Gardner, Andrew B},
	journal={arXiv preprint arXiv:1703.00410},
	year={2017}
}


@article{gong2017adversarial,
	title={Adversarial and clean data are not twins},
	author={Gong, Zhitao and Wang, Wenlu and Ku, Wei-Shinn},
	journal={arXiv preprint arXiv:1704.04960},
	year={2017}
}

@article{grosse2017statistical,
	title={On the (statistical) detection of adversarial examples},
	author={Grosse, Kathrin and Manoharan, Praveen and Papernot, Nicolas and Backes, Michael and McDaniel, Patrick},
	journal={arXiv preprint arXiv:1702.06280},
	year={2017}
}

@article{metzen2017detecting,
	title={On detecting adversarial perturbations},
	author={Metzen, Jan Hendrik and Genewein, Tim and Fischer, Volker and Bischoff, Bastian},
	journal={International Conference on Learning Representations ({ICLR})},
	year={2017}
}

@article{hendrycks2016early,
	title={Early methods for detecting adversarial images},
	author={Hendrycks, Dan and Gimpel, Kevin},
	journal={International Conference on Learning Representations ({ICLR})},
	year={2016}
}

@inproceedings{li2016adversarial,
  title={Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics},
  author={Li, Xin and Li, Fuxin},
  booktitle={2017 IEEE International Conference on Computer Vision (ICCV)},
  pages={5775--5783},
  year={2017},
  organization={IEEE}
}

@article{carlini2016defensive,
	title={Defensive distillation is not robust to adversarial examples},
	author={Carlini, Nicholas and Wagner, David},
	journal={arXiv preprint arXiv:1607.04311},
	year={2016}
}

@article{papernot2016effectiveness,
	title={On the effectiveness of defensive distillation},
	author={Papernot, Nicolas and McDaniel, Patrick},
	journal={arXiv preprint arXiv:1607.05113},
	year={2016}
}

@inproceedings{he2017adversarial,
  title={Adversarial example defenses: ensembles of weak defenses are not strong},
  author={He, Warren and Wei, James and Chen, Xinyun and Carlini, Nicholas and Song, Dawn},
  booktitle={Proceedings of the 11th {USENIX} Conference on Offensive Technologies},
  pages={15--15},
  year={2017},
  organization={{USENIX} Association}
}

@article{xu2017feature,
	title={Feature squeezing: Detecting adversarial examples in deep neural networks},
	author={Xu, Weilin and Evans, David and Qi, Yanjun},
	journal={Network and Distributed Systems Security Symposium ({NDSS})},
	year={2017}
}

@article{papernot2016towards,
	title={Towards the science of security and privacy in machine learning},
	author={Papernot, Nicolas and McDaniel, Patrick and Sinha, Arunesh and Wellman, Michael},
	journal={arXiv preprint arXiv:1611.03814},
	year={2016}
}

@article{Ian2015explaining,
	title={Explaining and Harnessing Adversarial Examples},
	author={ Goodfellow, Ian and Jonathon, Shlens and Christian,Szegedy},
	journal={International Conference on Learning Representations ({ICLR})},
	year={2015}
}


@inproceedings{madry2017towards,
  author    = {Aleksander Madry and
               Aleksandar Makelov and
               Ludwig Schmidt and
               Dimitris Tsipras and
               Adrian Vladu},
  title     = {Towards Deep Learning Models Resistant to Adversarial Attacks},
  booktitle = {Proceedings of the 6th International Conference on Learning Representations (ICLR)},
  address   = {Vancouver, Canada},
  year      = {2018}
}

@inproceedings{bhagoji2018enhancing,
	title={Enhancing robustness of machine learning systems via data transformations},
	author={Bhagoji, Arjun Nitin and Cullina, Daniel and Sitawarin, Chawin and Mittal, Prateek},
	booktitle={52nd Annual Conference on Information Sciences and Systems ({CISS})},
	pages={1--5},
	year={2018},
	organization={IEEE}
}

@inproceedings{meng2017magnet,
	title={Magnet: a two-pronged defense against adversarial examples},
	author={Meng, Dongyu and Chen, Hao},
	booktitle={Proceedings of the 2017 {ACM} {SIGSAC} Conference on Computer and Communications Security},
	pages={135--147},
	year={2017},
	organization={ACM}
}

@article{osadchy2017no,
	title={No Bot Expects the {DeepCAPTCHA}},
	author={Osadchy, Margarita and Hernandez-Castro, Julio and Gibson, Stuart and Dunkelman, Orr and P{\'e}rez-Cabo, Daniel},
	journal={{IEEE} Transactions on Information Forensics and Security},
	year={2017}
}

@article{konevcny2015federated,
  title={Federated optimization: Distributed optimization beyond the datacenter},
  author={Kone{\v{c}}n{\`y}, Jakub and McMahan, Brendan and Ramage, Daniel},
  journal={Conference on Neural Information Processing Systems ({NIPS})},
  year={2015}
}

@article{bagdasaryan2018backdoor,
  title={How To Backdoor Federated Learning},
  author={Bagdasaryan, Eugene and Veit, Andreas and Hua, Yiqing and Estrin, Deborah and Shmatikov, Vitaly},
  journal={arXiv preprint arXiv:1807.00459},
  year={2018}
}

@article{papernot2018scalable,
  title={Scalable Private Learning with PATE},
  author={Papernot, Nicolas and Song, Shuang and Mironov, Ilya and Raghunathan, Ananth and Talwar, Kunal and Erlingsson, {\'U}lfar},
  journal={International Conference on Learning Representations ({ICLR})},
  year={2018}
}
@article{papernot2016semi,
  title={Semi-supervised knowledge transfer for deep learning from private training data},
  author={Papernot, Nicolas and Abadi, Mart{\'\i}n and Erlingsson, Ulfar and Goodfellow, Ian and Talwar, Kunal},
  journal={International Conference on Learning Representations ({ICLR})},
  year={2016}
}


@inproceedings{sze2018hardware,
  title={Hardware for machine learning: Challenges and opportunities},
  author={Sze, Vivienne and Chen, Yu-Hsin and Emer, Joel and Suleiman, Amr and Zhang, Zhengdong},
  booktitle={Custom Integrated Circuits Conference ({CICC})},
  pages={1--8},
  year={2018},
  organization={IEEE}
}
@inproceedings{shokri2015privacy,
  title={Privacy-preserving deep learning},
  author={Shokri, Reza and Shmatikov, Vitaly},
  booktitle={Proceedings of the {ACM} {SIGSAC} conference on computer and communications security},
  pages={1310--1321},
  year={2015},
  organization={ACM}
}
@inproceedings{abadi2017protection,
  title={On the protection of private information in machine learning systems: Two recent approches},
  author={Abadi, Mart{\'\i}n and Erlingsson, Ulfar and Goodfellow, Ian and McMahan, H Brendan and Mironov, Ilya and Papernot, Nicolas and Talwar, Kunal and Zhang, Li},
  booktitle={Computer Security Foundations Symposium ({CSF})},
  pages={1--6},
  year={2017},
  organization={IEEE}
}
@inproceedings{abadi2016deep,
  author    = {Mart{\'{\i}}n Abadi and
               Andy Chu and
               Ian J. Goodfellow and
               H. Brendan McMahan and
               Ilya Mironov and
               Kunal Talwar and
               Li Zhang},
  title     = {Deep Learning with Differential Privacy},
  booktitle = {Proceedings of the 2016 {ACM} {SIGSAC} Conference on Computer and
               Communications Security (CCS)}, 
  address   = {Vienna, Austria},
  pages     = {308--318},
  year      = {2016}
}

@inproceedings{bolukbasi2017adaptive,
  title={Adaptive Neural Networks for Efficient Inference},
  author={Bolukbasi, Tolga and Wang, Joseph and Dekel, Ofer and Saligrama, Venkatesh},
  booktitle={International Conference on Machine Learning},
  pages={527--536},
  year={2017}
}

@article{ko2018edge,
  title={Edge-Host Partitioning of Deep Neural Networks with Feature Space Encoding for Resource-Constrained Internet-of-Things Platforms},
  author={Ko, Jong Hwan and Na, Taesik and Amir, Mohammad Faisal and Mukhopadhyay, Saibal},
  journal={arXiv preprint arXiv:1802.03835},
  year={2018}
}
@inproceedings{ba2014deep,
  title={Do deep nets really need to be deep?},
  author={Ba, Jimmy and Caruana, Rich},
  booktitle={Advances in neural information processing systems},
  pages={2654--2662},
  year={2014}
}
@article{zhu2018cloud,
  title={Cloud No Longer a Silver Bullet, Edge to the Rescue},
  author={Zhu, Yuhao and Wei, Gu-Yeon and Brooks, David},
  journal={arXiv preprint arXiv:1802.05943},
  year={2018}
}
@article{konevcny2016federated,
  title={Federated learning: Strategies for improving communication efficiency},
  author={Kone{\v{c}}n{\`y}, Jakub and McMahan, H Brendan and Yu, Felix X and Richt{\'a}rik, Peter and Suresh, Ananda Theertha and Bacon, Dave},
  journal={arXiv preprint arXiv:1610.05492},
  year={2016}
}

@inproceedings{song2017machine,
  title={Machine learning models that remember too much},
  author={Song, Congzheng and Ristenpart, Thomas and Shmatikov, Vitaly},
  booktitle={Proceedings of the {ACM} {SIGSAC} Conference on Computer and Communications Security},
  pages={587--601},
  year={2017},
  organization={ACM}
}
@inproceedings{yi2015fog,
  title={Fog computing: Platform and applications},
  author={Yi, Shanhe and Hao, Zijiang and Qin, Zhengrui and Li, Qun},
  booktitle={ Third {IEEE} Workshop on Hot Topics in Web Systems and Technologies ({HotWeb})},
  pages={73--78},
  year={2015},
  organization={IEEE}
}
@inproceedings{teerapittayanon2016branchynet,
  title={Branchynet: Fast inference via early exiting from deep neural networks},
  author={Teerapittayanon, Surat and McDanel, Bradley and Kung, HT},
  booktitle={International Conference on Pattern Recognition ({ICPR})},
  pages={2464--2469},
  year={2016},
  organization={IEEE}
}
@inproceedings{teerapittayanon2017distributed,
  title={Distributed deep neural networks over the cloud, the edge and end devices},
  author={Teerapittayanon, Surat and McDanel, Bradley and Kung, HT},
  booktitle={IEEE International Conference on Distributed Computing Systems ({ICDCS})},
  pages={328--339},
  year={2017},
  organization={IEEE}
}
@article{leroux2017cascading,
  title={The cascading neural network: building the Internet of Smart Things},
  author={Leroux, Sam and Bohez, Steven and De Coninck, Elias and Verbelen, Tim and Vankeirsbilck, Bert and Simoens, Pieter and Dhoedt, Bart},
  journal={Knowledge and Information Systems},
  volume={52},
  number={3},
  pages={791--814},
  year={2017},
  publisher={Springer}
}


@article{libbrecht2015machine,
  title={Machine learning applications in genetics and genomics},
  author={Libbrecht, Maxwell W and Noble, William Stafford},
  journal={Nature Reviews Genetics},
  volume={16},
  number={6},
  pages={321},
  year={2015},
  publisher={Nature Publishing Group}
}

@book{witten2016data,
  title={Data Mining: Practical machine learning tools and techniques},
  author={Witten, Ian H and Frank, Eibe and Hall, Mark A and Pal, Christopher J},
  year={2016},
  publisher={Morgan Kaufmann}
}

@inproceedings{lee2018techology,
  title={Techology trend of edge {AI}},
  author={Lee, Yen-Lin and Tsung, Pei-Kuei and Wu, Max},
  booktitle={International Symposium on {VLSI} Design, Automation and Test ({VLSI-DAT})},
  pages={1--2},
  year={2018},
  organization={IEEE}
}

@inproceedings{tang2015hierarchical,
  title={A hierarchical distributed fog computing architecture for big data analysis in smart cities},
  author={Tang, Bo and Chen, Zhen and Hefferman, Gerald and Wei, Tao and He, Haibo and Yang, Qing},
  booktitle={Proceedings of the {ASE} {BigData} \& {SocialInformatics}},
  pages={28},
  year={2015},
  organization={ACM}
}

@article{kurakin2016adversarial,
  title={Adversarial machine learning at scale},
  author={Kurakin, Alexey and Goodfellow, Ian and Bengio, Samy},
  journal={arXiv preprint arXiv:1611.01236},
  year={2016}
}


@article{robinson2018emerging,
  title={Emerging Technologies Challenging Current Legal Paradigms},
  author={Robinson, Walter K},
  journal={Minnesota Journal of Law, Science \& Technology},
  volume={19},
  number={2},
  pages={355},
  year={2018}
}

@article{ayinala2013place,
  title={An in-place {FFT} architecture for real-valued signals},
  author={Ayinala, Manohar and Lao, Yingjie and Parhi, Keshab K},
  journal={{IEEE} Transactions on Circuits and Systems II: Express Briefs},
  volume={60},
  number={10},
  pages={652--656},
  year={2013},
  publisher={IEEE}
}

@inproceedings{parhi2014canonic,
  title={Canonic real-valued {FFT} structures},
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@inproceedings{chen2019deepinspect,
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@inproceedings{qiao2019defending,
  author    = {Ximing Qiao and
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@article{turner2019label,
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@inproceedings{tan2019bypassing,
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@article{gu2019badnets,
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@inproceedings{bagdasaryan2021blind,
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@inproceedings{yao2019latent,
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@inproceedings{xie2019dba,
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@inproceedings{barni2019new,
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@inproceedings{liu2020reflection,
  author    = {Yunfei Liu and
               Xingjun Ma and
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@inproceedings{nguyen2021wanet,
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@inproceedings{doan2019adversarial,
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author = {Doan, Khoa D. and Reddy, Chandan K.},
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year = {2020},
isbn = {9781450370233},
publisher = {Association for Computing Machinery},
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               Radha Poovendran},
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  author    = {Mojan Javaheripi and
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  title     = {CleaNN: Accelerated Trojan Shield for Embedded Neural Networks},
  booktitle = {Proceedings of the {IEEE/ACM} International Conference On Computer Aided Design (ICCAD)},
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  year={2020}
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               Kimia Nadjahi and
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  title     = {Generalized Sliced Wasserstein Distances},
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  year      = {2019}
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@article{subedar2019deep,
  title={Deep probabilistic models to detect data poisoning attacks},
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  year={2019}
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@inproceedings{tang2021demon,
  author    = {Di Tang and
               XiaoFeng Wang and
               Haixu Tang and
               Kehuan Zhang},
  title     = {Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor
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  booktitle = {Proceedings of the 30th {USENIX} Security Symposium (USENIX Security)},
  pages     = {1541--1558},
  year      = {2021}
}

@inproceedings{tian2018deeptest,
  author    = {Yuchi Tian and
               Kexin Pei and
               Suman Jana and
               Baishakhi Ray},
  title     = {DeepTest: automated testing of deep-neural-network-driven autonomous
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  booktitle = {Proceedings of the 40th International Conference on Software Engineering (ICSE)},
  address   = {Gothenburg, Sweden},
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  year      = {2018}
}

@inproceedings{zhong2020backdoor,
  author    = {Haoti Zhong and
               Cong Liao and
               Anna Cinzia Squicciarini and
               Sencun Zhu and
               David J. Miller},
  title     = {Backdoor Embedding in Convolutional Neural Network Models via Invisible
               Perturbation},
  booktitle = {Proceedings of the tenth {ACM} Conference on Data and Application Security
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  address   = {New Orleans, LA},
  pages     = {97--108},
  year      = {2020}
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@inproceedings{zhu2019transferable,
  author    = {Chen Zhu and
               W. Ronny Huang and
               Hengduo Li and
               Gavin Taylor and
               Christoph Studer and
               Tom Goldstein},
  title     = {Transferable Clean-Label Poisoning Attacks on Deep Neural Nets},
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  address   = {Long Beach, CA},
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  year      = {2019}
}



@inproceedings{doan2021lira,
  author    = {Khoa Doan and
               Yingjie Lao and
               Weijie Zhao and
               Ping Li},
  title     = {{LIRA:} Learnable, Imperceptible and Robust Backdoor Attacks},
  booktitle = {Proceedings of the 2021 {IEEE/CVF} International Conference on Computer Vision (ICCV)},
  address   = {Montreal, Canada},
  pages     = {11946--11956},
  year      = {2021}
}



@inproceedings{bose2020adversarial,
  author    = {Avishek Joey Bose and
               Gauthier Gidel and
               Hugo Berard and
               Andre Cianflone and
               Pascal Vincent and
               Simon Lacoste{-}Julien and
               William L. Hamilton},
  title     = {Adversarial Example Games},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
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  year      = {2020}
}

@inproceedings{deshpande2018generative,
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               Ziyu Zhang and
               Alexander G. Schwing},
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  year      = {2018}
}

@inproceedings{nowozin2016f,
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@article{xue2022imperceptible,
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  year={2022}
}

@article{xue2022one,
  author    = {Mingfu Xue and
               Can He and
               Jian Wang and
               Weiqiang Liu},
  title     = {One-to-N {\&} N-to-One: Two Advanced Backdoor Attacks Against
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  journal   = {{IEEE} Trans. Dependable Secur. Comput.},
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  number    = {3},
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@inproceedings{li2021deeppayload,
  author    = {Yuanchun Li and
               Jiayi Hua and
               Haoyu Wang and
               Chunyang Chen and
               Yunxin Liu},
  title     = {{DeepPayload}: Black-box Backdoor Attack on Deep Learning Models through
               Neural Payload Injection},
  booktitle = {Proceedings of the 43rd {IEEE/ACM} International Conference on Software Engineering (ICSE)},
  address   = {Madrid, Spain},
  pages     = {263--274},
  year      = {2021}
}
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@inproceedings{kazemnejad2020paraphrase,
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  author    = {Jingwen Chen and
               Jiawei Chen and
               Hongyang Chao and
               Ming Yang},
  title     = {Image Blind Denoising With Generative Adversarial Network Based Noise
               Modeling},
  booktitle = {Proceedings of the 2018 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Salt Lake City, UT},
  pages     = {3155--3164},
  year      = {2018}
}

@inproceedings{xie2020self,
  author    = {Qizhe Xie and
               Minh{-}Thang Luong and
               Eduard H. Hovy and
               Quoc V. Le},
  title     = {Self-Training With Noisy Student Improves ImageNet Classification},
  booktitle = {Proceedings of the 2020 {IEEE/CVF} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Seattle, WA},
  pages     = {10684--10695},
  year      = {2020}
}

@inproceedings{tanaka2018joint,
  author    = {Daiki Tanaka and
               Daiki Ikami and
               Toshihiko Yamasaki and
               Kiyoharu Aizawa},
  title     = {Joint Optimization Framework for Learning With Noisy Labels},
  booktitle = {Proceedings of the 2018 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Salt Lake City, UT},
  pages     = {5552--5560},
  year      = {2018}
}


@inproceedings{chen2019looks,
  author    = {Chaofan Chen and
               Oscar Li and
               Daniel Tao and
               Alina Barnett and
               Cynthia Rudin and
               Jonathan Su},
  title     = {This Looks Like That: Deep Learning for Interpretable Image Recognition},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {Vancouver, Canada},
  pages     = {8928--8939},
  year      = {2019}
}

@inproceedings{li2018deep,
  author    = {Oscar Li and
               Hao Liu and
               Chaofan Chen and
               Cynthia Rudin},
  title     = {Deep Learning for Case-Based Reasoning Through Prototypes: {A} Neural
               Network That Explains Its Predictions},
  booktitle = {Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence (AAAI)},
  address   = {New Orleans, LA},
  pages     = {3530--3537},
  year      = {2018}
}

@inproceedings{tian2020rethinking,
  author    = {Yonglong Tian and
               Yue Wang and
               Dilip Krishnan and
               Joshua B. Tenenbaum and
               Phillip Isola},
  title     = {Rethinking Few-Shot Image Classification: {A} Good Embedding is All
               You Need?},
  booktitle = {Proceedings of the 16th European Conference on Computer Vision (ECCV), Part {XIV}}, 
  address   = {Glasgow,
               UK},
  pages     = {266--282},
  year      = {2020}
}

@InProceedings{houlsby2019parameter,
  author    = {Neil Houlsby and
               Andrei Giurgiu and
               Stanislaw Jastrzebski and
               Bruna Morrone and
               Quentin de Laroussilhe and
               Andrea Gesmundo and
               Mona Attariyan and
               Sylvain Gelly},
  title     = {Parameter-Efficient Transfer Learning for {NLP}},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning (ICML)},
  address   = {Long Beach, CA},
  pages     = {2790--2799},
  year      = {2019}
}

@inproceedings{zaken2022bitfit,
  author    = {Elad Ben Zaken and
               Yoav Goldberg and
               Shauli Ravfogel},
  title     = {{BitFit}: Simple Parameter-efficient Fine-tuning for Transformer-based
               Masked Language-models},
  booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational
               Linguistics (ACL)},
  address    = {Dublin, Ireland},
  pages     = {1--9},
  year      = {2022}
}


@inproceedings{zhao2021calibrate,
  author    = {Zihao Zhao and
               Eric Wallace and
               Shi Feng and
               Dan Klein and
               Sameer Singh},
  title     = {Calibrate Before Use: Improving Few-shot Performance of Language Models},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {12697--12706},
  year      = {2021}
}

@inproceedings{logan2022cutting,
  author    = {Robert L. Logan IV and
               Ivana Balazevic and
               Eric Wallace and
               Fabio Petroni and
               Sameer Singh and
               Sebastian Riedel},
  title     = {Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with
               Language Models},
  booktitle = {Findings of the Association for Computational Linguistics (ACL Findings)},
  address   = {Dublin, Ireland},
  pages     = {2824--2835},
  year      = {2022}
}

@article{zhang2021tip,
  title={Tip-adapter: Training-free clip-adapter for better vision-language modeling},
  author={Zhang, Renrui and Fang, Rongyao and Gao, Peng and Zhang, Wei and Li, Kunchang and Dai, Jifeng and Qiao, Yu and Li, Hongsheng},
  journal={arXiv preprint arXiv:2111.03930},
  year={2021}
}

@article{gao2021clip,
  title={Clip-adapter: Better vision-language models with feature adapters},
  author={Gao, Peng and Geng, Shijie and Zhang, Renrui and Ma, Teli and Fang, Rongyao and Zhang, Yongfeng and Li, Hongsheng and Qiao, Yu},
  journal={arXiv preprint arXiv:2110.04544},
  year={2021}
}

@inproceedings{jia2021scaling,
  author    = {Chao Jia and
               Yinfei Yang and
               Ye Xia and
               Yi{-}Ting Chen and
               Zarana Parekh and
               Hieu Pham and
               Quoc V. Le and
               Yun{-}Hsuan Sung and
               Zhen Li and
               Tom Duerig},
  title     = {Scaling Up Visual and Vision-Language Representation Learning With
               Noisy Text Supervision},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {4904--4916},
  year      = {2021}
}


@inproceedings{kim2021vilt,
  author    = {Wonjae Kim and
               Bokyung Son and
               Ildoo Kim},
  title     = {{ViLT}: Vision-and-Language Transformer Without Convolution or Region
               Supervision},
  booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {5583--5594},
  year      = {2021}
}

@article{liu2019roberta,
  title={Roberta: A robustly optimized bert pretraining approach},
  author={Liu, Yinhan and Ott, Myle and Goyal, Naman and Du, Jingfei and Joshi, Mandar and Chen, Danqi and Levy, Omer and Lewis, Mike and Zettlemoyer, Luke and Stoyanov, Veselin},
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  year={2019}
}

@inproceedings{lan2019albert,
  author    = {Zhenzhong Lan and
               Mingda Chen and
               Sebastian Goodman and
               Kevin Gimpel and
               Piyush Sharma and
               Radu Soricut},
  title     = {{ALBERT:} {A} Lite {BERT} for Self-supervised Learning of Language
               Representations},
  booktitle = {8th International Conference on Learning Representations, {ICLR} 2020,
               Addis Ababa, Ethiopia, April 26-30, 2020},
  publisher = {OpenReview.net},
  year      = {2020},
  url       = {https://openreview.net/forum?id=H1eA7AEtvS}
}


@inproceedings{li2021prefix,
  author    = {Xiang Lisa Li and
               Percy Liang},
  title     = {Prefix-Tuning: Optimizing Continuous Prompts for Generation},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational
               Linguistics and the 11th International Joint Conference on Natural
               Language Processing (ACL/IJCNLP)},
  address   = {Virtual
               Event},
  pages     = {4582--4597},
  year      = {2021}
}

@inproceedings{gao2021making,
  author    = {Tianyu Gao and
               Adam Fisch and
               Danqi Chen},
  title     = {Making Pre-trained Language Models Better Few-shot Learners},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational
               Linguistics and the 11th International Joint Conference on Natural
               Language Processing (ACL/IJCNLP)},
  address   = {Virtual
               Event},
  pages     = {3816--3830},
  year      = {2021}
}


@inproceedings{schick2021few,
  author    = {Timo Schick and
               Hinrich Sch{\"{u}}tze},
  title     = {Few-Shot Text Generation with Natural Language Instructions},
  booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural
               Language Processing (EMNLP)},
  address   = {Virtual Event / Punta Cana, Dominican
               Republic},
  pages     = {390--402},
  year      = {2021}
}

@inproceedings{sanh2022multitask,
  author    = {Victor Sanh and
               Albert Webson and
               Colin Raffel and
               Stephen Bach and
               Lintang Sutawika and
               Zaid Alyafeai and
               Antoine Chaffin and
               Arnaud Stiegler and
               Arun Raja and
               Manan Dey and
               M Saiful Bari and
               Canwen Xu and
               Urmish Thakker and
               Shanya Sharma Sharma and
               Eliza Szczechla and
               Taewoon Kim and
               Gunjan Chhablani and
               Nihal V. Nayak and
               Debajyoti Datta and
               Jonathan Chang and
               Mike Tian{-}Jian Jiang and
               Han Wang and
               Matteo Manica and
               Sheng Shen and
               Zheng Xin Yong and
               Harshit Pandey and
               Rachel Bawden and
               Thomas Wang and
               Trishala Neeraj and
               Jos Rozen and
               Abheesht Sharma and
               Andrea Santilli and
               Thibault F{\'{e}}vry and
               Jason Alan Fries and
               Ryan Teehan and
               Teven Le Scao and
               Stella Biderman and
               Leo Gao and
               Thomas Wolf and
               Alexander M. Rush},
  title     = {Multitask Prompted Training Enables Zero-Shot Task Generalization},
  booktitle = {Proceedings of the Tenth International Conference on Learning Representations (ICLR)},
  address   = {Virtual Event},
  year      = {2022}
}

@inproceedings{tsimpoukelli2021multimodal,
  author    = {Maria Tsimpoukelli and
               Jacob Menick and
               Serkan Cabi and
               S. M. Ali Eslami and
               Oriol Vinyals and
               Felix Hill},
  title     = {Multimodal Few-Shot Learning with Frozen Language Models},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {virtual},
  pages     = {200--212},
  year      = {2021}
}

@inproceedings{shin2020autoprompt,
  author    = {Taylor Shin and
               Yasaman Razeghi and
               Robert L. Logan IV and
               Eric Wallace and
               Sameer Singh},
  title     = {{AutoPrompt}: Eliciting Knowledge from Language Models with Automatically
               Generated Prompts},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural
               Language Processing (EMNLP)}, 
  address   = {Online},
  pages     = {4222--4235},
  year      = {2020}
}


@article{zhou2022learning,
  author    = {Kaiyang Zhou and
               Jingkang Yang and
               Chen Change Loy and
               Ziwei Liu},
  title     = {Learning to Prompt for Vision-Language Models},
  journal   = {Int. J. Comput. Vis.},
  volume    = {130},
  number    = {9},
  pages     = {2337--2348},
  year      = {2022}
}

@inproceedings{jin2022good,
  author    = {Woojeong Jin and
               Yu Cheng and
               Yelong Shen and
               Weizhu Chen and
               Xiang Ren},
  title     = {A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based
               Learning for Vision-Language Models},
  booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational
               Linguistics (ACL)},
  address    = {Dublin, Ireland},
  pages     = {2763--2775},
  year      = {2022}
}

@inproceedings{liang2022modular,
  author    = {Sheng Liang and
               Mengjie Zhao and
               Hinrich Sch{\"{u}}tze},
  title     = {Modular and Parameter-Efficient Multimodal Fusion with Prompting},
  booktitle = {Findings of the Association for Computational Linguistics (ACL Findings)},
  address   = {Dublin, Ireland},
  pages     = {2976--2985},
  year      = {2022}
}

@inproceedings{rao2022denseclip,
  author    = {Yongming Rao and
               Wenliang Zhao and
               Guangyi Chen and
               Yansong Tang and
               Zheng Zhu and
               Guan Huang and
               Jie Zhou and
               Jiwen Lu},
  title     = {{DenseCLIP}: Language-Guided Dense Prediction with Context-Aware Prompting},
  booktitle = {Proceedings of the {IEEE/CVF} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {New Orleans, LA},
  pages     = {18061--18070},
  year      = {2022}
}

@inproceedings{zhou2022cocoop,
  author    = {Kaiyang Zhou and
               Jingkang Yang and
               Chen Change Loy and
               Ziwei Liu},
  title     = {Conditional Prompt Learning for Vision-Language Models},
  booktitle = {Proceedings of the {IEEE/CVF} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {New Orleans, LA},
  pages     = {16795--16804},
  year      = {2022}
}

@article{jin2022instance,
  title={Instance-aware Prompt Learning for Language Understanding and Generation},
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  year={2022}
}

@article{qin2021learning,
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  author    = {Zexuan Zhong and
               Dan Friedman and
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  pages     = {2463--2473}
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@article{zhao2022constrained,
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@inproceedings{yu2019linear,
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               Rong Jin and
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@inproceedings{chen2022convergence,
  author    = {Xiangyi Chen and
               Belhal Karimi and
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  year      = {2022}
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@inproceedings{zhao2022communication,
  author       = {Weijie Zhao and
                  Xuewu Jiao and
                  Mingqing Hu and
                  Xiaoyun Li and
                  Xiangyu Zhang and
                  Ping Li},
  title        = {{PaddleBox}: Communication-Efficient TeraByte-Scale Model Training Framework
                  for Online Advertising},
  booktitle = {Proceedings of the {IEEE} International Conference on Big Data (IEEE BigData)},
  address  = {Osaka, Japan},
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  year      = {2022}
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@inproceedings{zhao2022featurebox,
  author    = {Weijie Zhao and Xuewu Jiao and Xinsheng Luo and Jingxue Li and Belhal Karimi and Ping Li},
  title     = {{FeatureBox}: Feature Engineering on {GPUs}  for Massive-Scale Ads Systems},
  booktitle = {Proceedings of the {IEEE} International Conference on Big Data (IEEE BigData)},
  address  = {Osaka, Japan},
  year      = {2022}
}

@inproceedings{mohri2018agnostic,
  author    = {Mehryar Mohri and
               Gary Sivek and
               Ananda Theertha Suresh},
  title     = {Agnostic Federated Learning},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning (ICML)},
  address  = {Long Beach, CA},
  pages     = {4615--4625},
  year      = {2019}
}

@inproceedings{liu2020fedvision,
  author    = {Yang Liu and
               Anbu Huang and
               Yun Luo and
               He Huang and
               Youzhi Liu and
               Yuanyuan Chen and
               Lican Feng and
               Tianjian Chen and
               Han Yu and
               Qiang Yang},
  title     = {{FedVision}: An Online Visual Object Detection Platform Powered by Federated
               Learning},
  booktitle = {Proceedings of the Thirty-Fourth {AAAI} Conference on Artificial Intelligence (AAAI)},
  address  = {New York, NY},
  pages     = {13172--13179},
  year      = {2020}
}


@article{rieke2020future,
  title={The future of digital health with federated learning},
  author={Rieke, Nicola and Hancox, Jonny and Li, Wenqi and Milletari, Fausto and Roth, Holger R and Albarqouni, Shadi and Bakas, Spyridon and Galtier, Mathieu N and Landman, Bennett A and Maier-Hein, Klaus and others},
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@article{khan2021federated,
  author    = {Latif U. Khan and
               Walid Saad and
               Zhu Han and
               Ekram Hossain and
               Choong Seon Hong},
  title     = {Federated Learning for Internet of Things: Recent Advances, Taxonomy,
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  volume    = {23},
  number    = {3},
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  year      = {2021}
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@inproceedings{stich2019local,
  author    = {Sebastian U. Stich},
  title     = {Local {SGD} Converges Fast and Communicates Little},
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  address  = {New Orleans, LA},
  year      = {2019}
}

@inproceedings{marfoq2020throughput,
  author    = {Othmane Marfoq and
               Chuan Xu and
               Giovanni Neglia and
               Richard Vidal},
  title     = {Throughput-Optimal Topology Design for Cross-Silo Federated Learning},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
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  year      = {2020}
}

@inproceedings{huang2021personalized,
  author    = {Yutao Huang and
               Lingyang Chu and
               Zirui Zhou and
               Lanjun Wang and
               Jiangchuan Liu and
               Jian Pei and
               Yong Zhang},
  title     = {Personalized Cross-Silo Federated Learning on Non-{IID} Data},
  booktitle = {Proceedings of the Thirty-Fifth {AAAI} Conference on Artificial Intelligence (AAAI)}, 
  address  = {Virtual Event},
  pages     = {7865--7873},
  year      = {2021}
}

@inproceedings{karimireddy2021breaking,
  author    = {Sai Praneeth Karimireddy and
               Martin Jaggi and
               Satyen Kale and
               Mehryar Mohri and
               Sashank J. Reddi and
               Sebastian U. Stich and
               Ananda Theertha Suresh},
  title     = {Breaking the centralized barrier for cross-device federated learning},
  booktitle = {Advances in Neural Information Processing Systems  (NeurIPS)},
  address  = {virtual},
  pages     = {28663--28676},
  year      = {2021}
}

@article{amiri2020federated,
  author    = {Mohammad Mohammadi Amiri and
               Deniz G{\"{u}}nd{\"{u}}z},
  title     = {Federated Learning Over Wireless Fading Channels},
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  volume    = {19},
  number    = {5},
  pages     = {3546--3557},
  year      = {2020}
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@inproceedings{li2020convergence,
  author    = {Xiang Li and
               Kaixuan Huang and
               Wenhao Yang and
               Shusen Wang and
               Zhihua Zhang},
  title     = {On the Convergence of {FedAvg} on Non-{IID} Data},
  booktitle = {Proceedings of the 8th International Conference on Learning Representations (ICLR)},
  address  = {Addis Ababa, Ethiopia},
  year      = {2020}
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@article{li2020federated,
  author    = {Tian Li and
               Anit Kumar Sahu and
               Ameet Talwalkar and
               Virginia Smith},
  title     = {Federated Learning: Challenges, Methods, and Future Directions},
  journal   = {{IEEE} Signal Process. Mag.},
  volume    = {37},
  number    = {3},
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  year      = {2020}
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@inproceedings{charles2021large,
  author    = {Zachary Charles and
               Zachary Garrett and
               Zhouyuan Huo and
               Sergei Shmulyian and
               Virginia Smith},
  title     = {On Large-Cohort Training for Federated Learning},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address  =  {virtual},
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  year      = {2021}
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@inproceedings{reisizadeh2020fedpaq,
  author    = {Amirhossein Reisizadeh and
               Aryan Mokhtari and
               Hamed Hassani and
               Ali Jadbabaie and
               Ramtin Pedarsani},
  title     = {{FedPAQ}: {A} Communication-Efficient Federated Learning Method with
               Periodic Averaging and Quantization},
  booktitle = {Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)},
  address  = {Online [Palermo, Sicily, Italy]},
  pages     = {2021--2031},
  year      = {2020}
}

@inproceedings{haddadpour2021federated,
  author    = {Farzin Haddadpour and
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               Aryan Mokhtari and
               Mehrdad Mahdavi},
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  year      = {2021}
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@inproceedings{dettmers20168,
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@inproceedings{bernstein2019signsgd,
  author    = {Jeremy Bernstein and
               Jiawei Zhao and
               Kamyar Azizzadenesheli and
               Anima Anandkumar},
  title     = {{signSGD} with Majority Vote is Communication Efficient and Fault Tolerant},
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}


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               Deepesh Data and
               Can Karakus and
               Suhas N. Diggavi},
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               and Local Computations},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
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}

@inproceedings{yu2018gradiveq,
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               Songze Li and
               Youjie Li and
               Nam Sung Kim and
               Alexander G. Schwing and
               Murali Annavaram and
               Salman Avestimehr},
  title     = {{GradiVeQ}: Vector Quantization for Bandwidth-Efficient Gradient Aggregation
               in Distributed {CNN} Training},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
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}

@inproceedings{vogels2019powersgd,
  author    = {Thijs Vogels and
               Sai Praneeth Karimireddy and
               Martin Jaggi},
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  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
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  year      = {2019}
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               Hui Qian},
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@inproceedings{zheng2019communication,
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               Ilyas Fatkhullin},
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               George J. Pappas and
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  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
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  title     = {{SCAFFOLD:} Stochastic Controlled Averaging for Federated Learning},
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@inproceedings{bernstein2018signsgd,
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               Animashree Anandkumar},
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@inproceedings{xu2022texture,
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@inproceedings{liu2022cross,
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               Tan Yu and
               Hanyu Peng and
               Mingming Sun and
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@inproceedings{yu2022cross,
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               Hongliang Fei and
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  address  = {Madrid, Spain},
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@inproceedings{yu2021assorted,
  author    = {Tan Yu and
               Yi Yang and
               Hongliang Fei and
               Yi Li and
               Xiaodong Chen and
               Ping Li},
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  address  = {Virtual Event, Queensland, Australia},
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@inproceedings{fei2021cross,
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               Tan Yu and
               Ping Li},
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  year      = {2021}
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@inproceedings{yu2021heterogeneous,
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               Yi Yang and
               Yi Li and
               Lin Liu and
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               Ping Li},
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  address  = {Virtual Event, Canada},
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  year      = {2021}
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@inproceedings{yu2021cross,
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               Hongliang Fei and
               Ping Li},
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  year      = {2021}
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@inproceedings{yu2022multi,
  author    = {Tan Yu and
               Jie Liu and
               Zhipeng Jin and
               Yi Yang and
               Hongliang Fei and
               Ping Li},
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  address  = {Atlanta, GA},
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  year      = {2022}
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@inproceedings{yu2022u,
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@misc{dong2021cswin,
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  title     = {Multiscale Vision Transformers},
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@article{Anonymous:InpnHrAT,
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@inproceedings{doan2020daba,
author = {Doan, Khoa D. and Reddy, Chandan K.},
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publisher = {Association for Computing Machinery},
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series = {WWW '20}
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@inproceedings{Proc:Zhao_MLSys20,
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               Ping Li},
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@inproceedings{Proc:Xu_SIGMOD21,
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@inproceedings{nguyen2021distributional,
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@inproceedings{zhong2020backdoor,
  author    = {Haoti Zhong and
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  address   = {New Orleans, LA},
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@inproceedings{zhu2019transferable,
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  year      = {2019}
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@InProceedings{Doan_2021_ICCV,
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               Pascal Vincent and
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               William L. Hamilton},
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  year      = {2020}
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  year      = {2018}
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@inproceedings{gkelios2021investigating,
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@article{khan2021transformers,
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@inproceedings{mao2021towards,
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@inproceedings{benz2021adversarial,
  author    = {Philipp Benz and
               Soomin Ham and
               Chaoning Zhang and
               Adil Karjauv and
               In So Kweon},
  title     = {Adversarial Robustness Comparison of Vision Transformer and {MLP-Mixer}
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  address   = {Online},
  pages     = {25},
  year      = {2021}
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               Daniel Glasner and
               Daliang Li and
               Thomas Unterthiner and
               Andreas Veit},
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@inproceedings{naseer2021intriguing,
  author    = {Muzammal Naseer and
               Kanchana Ranasinghe and
               Salman Khan and
               Munawar Hayat and
               Fahad Shahbaz Khan and
               Ming{-}Hsuan Yang},
  title     = {Intriguing Properties of Vision Transformers},
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  author    = {Kaleel Mahmood and
               Rigel Mahmood and
               Marten van Dijk},
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  year      = {2021}
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  year={2021}
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@inproceedings{naseer2022improving,
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               Salman Khan and
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  year={2021}
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@inproceedings{kudekar2010effect,
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@article{schniter2015compressive,
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@inproceedings{rangan2011generalized,
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@inproceedings{ma2017analysis,
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%% LaTeX2e file `quickbib.bib'
%% generated by the `filecontents' environment
%% from source `dense-subhypergraph-note' on 2020/09/08.



%%


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  volume    = {5},
  number    = {1},
  pages     = {1--19},
  year      = {2021}
}

@inproceedings{leroy2019federated,
  author    = {David Leroy and
               Alice Coucke and
               Thibaut Lavril and
               Thibault Gisselbrecht and
               Joseph Dureau},
  title     = {Federated Learning for Keyword Spotting},
  booktitle = {Proceedings of the {IEEE} International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  address   = {Brighton, UK},
  pages     = {6341--6345},
  year      = {2019}
}

@inproceedings{bonawitz2019towards,
  author    = {Kallista A. Bonawitz and
               Hubert Eichner and
               Wolfgang Grieskamp and
               Dzmitry Huba and
               Alex Ingerman and
               Vladimir Ivanov and
               Chlo{\'{e}} Kiddon and
               Jakub Kone{\v{c}}n{\'y} and
               Stefano Mazzocchi and
               Brendan McMahan and
               Timon Van Overveldt and
               David Petrou and
               Daniel Ramage and
               Jason Roselander},
  title     = {Towards Federated Learning at Scale: System Design},
  booktitle = {Proceedings of Machine Learning and Systems (MLSys)},
  address  = {Stanford,
               CA},
  year      = {2019}
}

@inproceedings{woodworth2020is,
  author    = {Blake E. Woodworth and
               Kumar Kshitij Patel and
               Sebastian U. Stich and
               Zhen Dai and
               Brian Bullins and
               H. Brendan McMahan and
               Ohad Shamir and
               Nathan Srebro},
  title     = {Is Local {SGD} Better than Minibatch {SGD}?},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning (ICML)},
  address   = {Virtual Event},
  pages     = {10334--10343},
  year      = {2020}
}

@article{sahu2018convergence,
  author    = {Anit Kumar Sahu and
               Tian Li and
               Maziar Sanjabi and
               Manzil Zaheer and
               Ameet Talwalkar and
               Virginia Smith},
  title     = {On the Convergence of Federated Optimization in Heterogeneous Networks},
  year      = {2018}
}

@inproceedings{wang2020slowmo,
  author    = {Jianyu Wang and
               Vinayak Tantia and
               Nicolas Ballas and
               Michael G. Rabbat},
  title     = {{SlowMo}: Improving Communication-Efficient Distributed {SGD} with Slow
               Momentum},
  booktitle = {Proceedings of the 8th International Conference on Learning Representations (ICLR)},
  address   = {
               Addis Ababa, Ethiopia},
  year      = {2020}
}





@article{bottou2018optimization,
  title={Optimization methods for large-scale machine learning},
  author={Bottou, L{\'e}on and Curtis, Frank E and Nocedal, Jorge},
  journal={Siam Review},
  volume={60},
  number={2},
  pages={223--311},
  year={2018},
  publisher={SIAM}
}

@article{bhagoji2018analyzing,
  title={Analyzing federated learning through an adversarial lens},
  author={Bhagoji, Arjun Nitin and Chakraborty, Supriyo and Mittal, Prateek and Calo, Seraphin},
  journal={arXiv preprint arXiv:1811.12470},
  year={2018}
}
@article{khaled2019first,
  title={First Analysis of Local GD on Heterogeneous Data},
  author={Khaled, Ahmed and Mishchenko, Konstantin and Richt{\'a}rik, Peter},
  journal={arXiv preprint arXiv:1909.04715},
  year={2019}
}


@article{yang2014regret,
  title={Regret bounded by gradual variation for online convex optimization},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Zhu, Shenghuo},
  journal={Machine learning},
  year={2014}
}

@article{mahdavi2012trading,
  title={Trading regret for efficiency: online convex optimization with long term constraints},
  author={Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  journal={Journal of Machine Learning Research},
  volume={13},
  number={Sep},
  pages={2503--2528},
  year={2012}
}
@inproceedings{jiang2017collaborative,
  title={Collaborative deep learning in fixed topology networks},
  author={Jiang, Zhanhong and Balu, Aditya and Hegde, Chinmay and Sarkar, Soumik},
  booktitle={Advances in Neural Information Processing Systems},
  pages={5904--5914},
  year={2017}
}




@inproceedings{haddadpour2019trading,
  author    = {Farzin Haddadpour and
               Mohammad Mahdi Kamani and
               Mehrdad Mahdavi and
               Viveck R. Cadambe},
  title     = {Trading Redundancy for Communication: Speeding up Distributed {SGD}
               for Non-convex Optimization},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning (ICML)},
  address  = {Long Beach, CA},
  pages     = {2545--2554},
  year      = {2019}
}
@inproceedings{lian2017can,
  title={Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent},
  author={Lian, Xiangru and Zhang, Ce and Zhang, Huan and Hsieh, Cho-Jui and Zhang, Wei and Liu, Ji},
  booktitle={Advances in Neural Information Processing Systems},
  pages={5330--5340},
  year={2017}
}
@inproceedings{li2019convergence,
  author    = {Xiang Li and
               Kaixuan Huang and
               Wenhao Yang and
               Shusen Wang and
               Zhihua Zhang},
  title     = {On the Convergence of FedAvg on Non-IID Data},
  booktitle = {Proceedings of the 8th International Conference on Learning Representations (ICLR)},
  address  = {Ethiopia},
  year      = {2020}
}

@inproceedings{ho2013more,
  title={More effective distributed ml via a stale synchronous parallel parameter server},
  author={Ho, Qirong and Cipar, James and Cui, Henggang and Lee, Seunghak and Kim, Jin Kyu and Gibbons, Phillip B and Gibson, Garth A and Ganger, Greg and Xing, Eric P},
  booktitle={Advances in neural information processing systems},
  pages={1223--1231},
  year={2013}
}

@article{nisan2001algorithmic,
  title={Algorithmic mechanism design},
  author={Nisan, Noam and Ronen, Amir},
  journal={Games and Economic behavior},
  volume={35},
  number={1-2},
  pages={166--196},
  year={2001},
  publisher={Elsevier}
}

@article{stich2018local,
  title={Local SGD converges fast and communicates little},
  author={Stich, Sebastian U},
  journal={arXiv preprint arXiv:1805.09767},
  year={2018}
}

@article{mahdavi2012trading,
  title={Trading regret for efficiency: online convex optimization with long term constraints},
  author={Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  journal={Journal of Machine Learning Research},
  volume={13},
  number={Sep},
  pages={2503--2528},
  year={2012}
}

@article{mohri2019agnostic,
  title={Agnostic federated learning},
  author={Mohri, Mehryar and Sivek, Gary and Suresh, Ananda Theertha},
  journal={arXiv preprint arXiv:1902.00146},
  year={2019}
}

@inproceedings{multile-kernel-noisy,
  author    = {Tianbao Yang and
               Mehrdad Mahdavi and
               Rong Jin and
               Lijun Zhang and
               Yang Zhou},
  title     = {Multiple Kernel Learning from Noisy Labels by Stochastic Programming},
  booktitle = {Proceedings of the 29th International Conference on Machine Learning (ICML)},
  year      = {2012},
}
@article{linearbandit,
  title={Linear Bandits Against Low Rank Adversaries},
  author={Mahdavi, Mehrdad},
  journal={Technical report},
  year={2016}
}
@article{yang2012efficient,
  author    = {Tianbao Yang and
               Mehrdad Mahdavi and
               Rong Jin and
               Shenghuo Zhu},
  title     = {An efficient primal dual prox method for non-smooth optimization},
  journal   = {Machine Learning},
  volume    = {98},
  number    = {3},
  pages     = {369--406},
  year      = {2015}
}
@inproceedings{johnson2013accelerating,
  title={Accelerating stochastic gradient descent using predictive variance reduction},
  author={Johnson, Rie and Zhang, Tong},
  booktitle={Advances in Neural Information Processing Systems},
  pages={315--323},
  year={2013}
}
@article{mahdavi2014exploiting,
  title={Exploiting Smoothness in Statistical Learning, Sequential Prediction, and Stochastic Optimization},
  author={Mahdavi, Mehrdad},
  journal={P.h.D Thesis},
  year={2014}
}
@inproceedings{mahdavi2015lower,
  title={Lower and upper bounds on the generalization of stochastic exponentially concave optimization},
  author={Mahdavi, Mehrdad and Zhang, Lijun and Jin, Rong},
  booktitle={COLT},
  pages={1305--1320},
  year={2015}
}
@inproceedings{meshi2015smooth,
  title={Smooth and Strong: MAP Inference with Linear Convergence},
  author={Meshi, Ofer and Mahdavi, Mehrdad and Schwing, Alex},
  booktitle={Advances in Neural Information Processing Systems (NIPS)},
  pages={298--306},
  year={2015}
}
@inproceedings{meshi2016train,
  title={Train and Test Tightness of LP Relaxations in Structured Prediction},
  author={Meshi, Ofer and Mahdavi, Mehrdad and Weller, Adrian and Sontag, David},
  booktitle={Proceedings of The 33rd International Conference on Machine Learning (ICML)},
  year={2016}
}
@article{wang2016sketching,
  title={Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data},
  author={Wang, Jialei and Lee, Jason D and Mahdavi, Mehrdad and Kolar, Mladen and Srebro, Nathan},
  journal={arXiv preprint arXiv:1610.03045},
  year={2016}
}
@article{zhang2014random,
  title={Random Projections for Classification: A Recovery Approach},
  author={Zhang, Lijun and Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao and Zhu, Shenghuo},
  journal={IEEE transactions on Infromation Theory},
  volume={60},
  number={11},
  year={2014}
}
@article{forsati2014matrix,
  title={Matrix Factorization with Explicit Trust and Distrust Side Information for Improved Social Recommendation},
  author={Forsati, Rana and Mahdavi, Mehrdad and Shamsfard, Mehrnoush and Sarwat, Mohamed},
  journal={ACM Transactions on Information Systems (TOIS)},
  volume={32},
  number={4},
  pages={17},
  year={2014},
  publisher={ACM}
}
@article{chandrasekaran2013computational,
  title={Computational and statistical tradeoffs via convex relaxation},
  author={Chandrasekaran, Venkat and Jordan, Michael I},
  journal={Proceedings of the National Academy of Sciences},
  volume={110},
  number={13},
  pages={E1181--E1190},
  year={2013},
  publisher={National Acad Sciences}
}

@article{omran2008global,
  title={Global-best harmony search},
  author={Omran, Mahamed  and Mahdavi, Mehrdad},
  journal={Applied Mathematics and Computation},
  volume={198},
  number={2},
  pages={643--656},
  year={2008},
  publisher={Elsevier}
}

@article{mahdavi2007improved,
  title={An improved harmony search algorithm for solving optimization problems},
  author={Mahdavi, Mehrdad and Fesanghary, Mohammad and Damangir, E},
  journal={Applied Mathematics and Computation},
  volume={188},
  number={2},
  pages={1567--1579},
  year={2007},
  publisher={Elsevier}
}


@article{omran2008global,
  title={Global-best harmony search},
  author={Omran, Mahamed  and Mahdavi, Mehrdad},
  journal={Applied Mathematics and Computation},
  volume={198},
  number={2},
  pages={643--656},
  year={2008},
  publisher={Elsevier}
}



@article{mahdavi2009harmony,
  title={Harmony K-means algorithm for document clustering},
  author={Mahdavi, Mehrdad and Abolhassani, Hassan},
  journal={Data Mining and Knowledge Discovery},
  volume={18},
  number={3},
  pages={370--391},
  year={2009},
  publisher={Springer}
}

@inproceedings{williams2001using,
  title={Using the Nystr{\"o}m method to speed up kernel machines},
  author={Williams, Christopher and Seeger, Matthias},
  booktitle={Advances in Neural Information Processing Systems 13},
  year={2001},
  organization={Citeseer}
}

@book{nesterov2004introductory,
  title={Introductory lectures on convex optimization: A basic course},
  author={Nesterov, Yurii},
  volume={87},
  year={2004},
  publisher={Springer}
}

@book{scholkopf2002learning,
  title={Learning with kernels},
  author={Sch{\"o}lkopf, Bernhard and Smola, Alexander J},
  year={2002},
  publisher={ÒTheÓ MIT Press}
}

@book{national2013Frontiers,
  title={Frontiers in Massive Data Analysis},
  author={Committee on the Analysis of Massive Data; Committee on Applied and Theoretical Statistics; Board on Mathematical Sciences and Their Applications; Division on Engineering and Physical Sciences; National Research Council},
  isbn={9780309287784},
  url={http://www.nap.edu/openbook.php?record_id=18374},
  year={2013},
  publisher={The National Academies Press}
}

@article{mahdavi2007improved,
  title={An Improved Harmony Search Algorithm for Solving Optimization Problems},
  author={Mahdavi, Mehrdad and Fesanghary, M and Damangir, E},
  journal={Applied Mathematics and Computation},
  volume={188},
  number={2},
  pages={1567--1579},
  year={2007},
  publisher={Elsevier}
}

@article{omran2008global,
  title={Global-best harmony search},
  author={Omran, Mahamed GH and Mahdavi, Mehrdad},
  journal={Applied Mathematics and Computation},
  volume={198},
  number={2},
  pages={643--656},
  year={2008},
  publisher={Elsevier}
}

@article{forsati2008harmony,
  title={Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing},
  author={Forsati, R and Haghighat, AT and Mahdavi, M},
  journal={Computer Communications},
  volume={31},
  number={10},
  pages={2505--2519},
  year={2008},
  publisher={Elsevier}
}

@article{mahdavi2009harmony,
  title={Harmony K-means algorithm for document clustering},
  author={Mahdavi, Mehrdad and Abolhassani, Hassan},
  journal={Data Mining and Knowledge Discovery},
  volume={18},
  number={3},
  pages={370--391},
  year={2009},
  publisher={Springer US}
}

@article{mahdavi2008novel,
  title={Novel meta-heuristic algorithms for clustering web documents},
  author={Mahdavi, Mehrdad and Chehreghani, M Haghir and Abolhassani, Hassan and Forsati, Rana},
  journal={Applied Mathematics and Computation},
  volume={201},
  number={1},
  pages={441--451},
  year={2008},
  publisher={Elsevier}
}

@inproceedings{forsati2008efficient,
  title={An efficient algorithm for bandwidth-delay constrained least cost multicast routing},
  author={Forsati, Rana and Mahdavi, Mehrdad and Haghighat, Abolfazl Torghy and Ghariniyat, A},
  booktitle={Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on},
  pages={001641--001646},
  year={2008},
  organization={IEEE}
}

@inproceedings{forsati2009effective,
  title={Effective page recommendation algorithms based on distributed learning automata},
  author={Forsati, Rana and Rahbar, Afsaneh and Mahdavi, Mehrdad},
  booktitle={Computing in the Global Information Technology, 2009. ICCGI'09. Fourth International Multi-Conference on},
  pages={41--46},
  year={2009},
  organization={IEEE}
}

@incollection{mahdavi2009bandwidth,
  title={Bandwidth-Delay Constrained Least Cost Multicast Routing for Multimedia Communication},
  author={Mahdavi, Mehrdad and Forsati, Rana and Movaghar, Ali},
  booktitle={Advances in Computer Science and Engineering},
  pages={737--740},
  year={2009},
  publisher={Springer Berlin Heidelberg}
}

@article{khodamoradi2007upper,
  title={Upper Bounding the Price of Anarchy in Atomic Splittable Selfish Routing},
  author={Khodamoradi, Kamyar and Mahdavi, Mehrdad and Ghodsi, Mohammad},
  year={2007}
}

@incollection{mahdavi2009solving,
  title={Solving NP-Complete Problems by Harmony Search},
  author={Mahdavi, Mehrdad},
  booktitle={Music-Inspired Harmony Search Algorithm},
  pages={53--70},
  year={2009},
  publisher={Springer Berlin Heidelberg}
}

@article{yang2011regret,
  title={Regret Bound by Variation for Online Convex Optimization},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Zhu, Shenghuo},
  journal={Arxiv preprint arXiv:1111.6337},
  year={2011}
}

@article{mahdavi2011trading,
  title={Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints},
  author={Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  journal={Arxiv preprint arXiv:1111.6082},
  year={2011}
}


@article{forsati2007web,
  title={Web page personalization based on distributed learning automata},
  author={Forsati, R and Meybodi, MR and Mahdavi, M},
  journal={Proc. IKT, Ferdowsi University of Mashad, Mashad, Iran},
  year={2007}
}

@article{mahdavi2012efficient,
  title={Efficient constrained regret minimization},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  journal={arXiv preprint arXiv:1205.2265},
  year={2012}
}

@article{yang2012multiple,
  title={Multiple Kernel Learning from Noisy Labels by Stochastic Programming},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Zhang, Lijun and Zhou, Yang},
  journal={ICML},
  year={2012}
}

@inproceedings{chiang2012online,
  title={Online Optimization with Gradual Variations.},
  author={Yang, Tianbao  and Mahdavi, Mehrdad and  Jin, Rong and Zhu, Shenghuo},
  booktitle={Conference on Learning Theory (COLT)},
  year={2012}
}

@inproceedings{yang2012online,
  title={Online Kernel Selection: Algorithms and Evaluations.},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Yi, Jinfeng and Hoi, Steven CH},
  booktitle={AAAI},
  year={2012}
}

@article{forsati2012efficient,
  title={Efficient stochastic algorithms for document clustering},
  author={Forsati, Rana and Mahdavi, Mehrdad and Shamsfard, Mehrnoosh and Reza Meybodi, Mohammad},
  journal={Information Sciences},
  year={2012},
  publisher={Elsevier}
}

@article{fesanghary2008hybridizing,
  title={Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems},
  author={Fesanghary, M and Mahdavi, M and Minary-Jolandan, M and Alizadeh, Y},
  journal={Computer methods in applied mechanics and engineering},
  volume={197},
  number={33},
  pages={3080--3091},
  year={2008},
  publisher={North-Holland}
}

@inproceedings{forsati2008web,
  title={Web page clustering using harmony search optimization},
  author={Forsati, Rana and Mahdavi, Mehrdad and Kangavari, Mohammadreza and Safarkhani, Banafsheh},
  booktitle={Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on},
  pages={001601--001604},
  year={2008},
  organization={IEEE}
}

@inproceedings{forsati2008hybridization,
  title={Hybridization of K-means and harmony search methods for web page clustering},
  author={Forsati, Rana and Meybodi, Mohammad Reza and Mahdavi, Mehrdad and Neiat, Azadeh Ghari},
  booktitle={Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT'08. IEEE/WIC/ACM International Conference on},
  volume={1},
  pages={329--335},
  year={2008},
  organization={IEEE}
}

@incollection{forsati2010web,
  title={Web text mining using harmony search},
  author={Forsati, Rana and Mahdavi, Mehrdad},
  booktitle={Recent advances in harmony search algorithm},
  pages={51--64},
  year={2010},
  publisher={Springer Berlin Heidelberg}
}

@article{mahdavi2012improved,
  title={An Improved Bound for the Nystrom Method for Large Eigengap},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  journal={arXiv preprint arXiv:1209.0001},
  year={2012}
}

@inproceedings{yi2012robust,
  title={Robust Ensemble Clustering by Matrix Completion},
  author={Yi, Jinfeng and Yang, Tianbao and Jin, Rong and Jain, Anil K and Mahdavi, Mehrdad},
  booktitle={ICDM},
  year={2012},
  organization={IEEE}
}

@inproceedings{yang2012nystrom,
  title={Nystrom Method vs Random Fourier Features: A Theoretical and Empirical Comparison},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Li, Yu-Feng and Jin, Rong and Zhou, Zhi-Hua},
  year={2012},
  booktitle={Advances in Neural Information Processing Systems 25 (NIPS)},
}

@inproceedings{mahdavi2012online,
  title={Online Decision Making under Stochastic Constraints},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  booktitle={Discrete Optimization in Machine Learning (DISCML), NIPS 2012 Workshop},
  year={2012}
}

@article{mahdavi2012trading,
  title={Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints},
  author={Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  journal={Journal of Machine Learning Research (JMLR)},
  volume={13},
  pages={2503--2528},
  year={2012},
  publisher={MIT Press}
}

@inproceedings{mahdavi2012stochastic,
  title={Stochastic Gradient Descent with Only One Projection},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong and Zhu, Shenghuo and Yi, Jinfeng},
  booktitle={Advances in Neural Information Processing Systems 25 (NIPS)},
  year={2012}
}

@article{mahdavi2012online,
  title={Online Stochastic Optimization with Multiple Objectives},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  journal={arXiv preprint arXiv:1211.6013},
  year={2012}
}


@article{jin2013sparse,
  title={Sparse Multiple Kernel Learning with Geometric Convergence Rate},
  author={Jin, Rong and Yang, Tianbao and Mahdavi, Mehrdad},
  journal={arXiv preprint arXiv:1302.0315},
  year={2013}
}


@inproceedings{zhang2013recovering,
  title={Recovering the Optimal Solution by Dual Random Projection},
  author={Zhang, Lijun and Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  booktitle={Conference on Learning Theory (COLT)},
  year={2013}
}


@inproceedings{mahdavi2013passive,
  title={Passive Learning with Target Risk},
  author={Mahdavi, Mehrdad and Jin, Rong},
  booktitle={Conference on Learning Theory (COLT)},
  year={2013}
}

@article{mahdavi2012high,
  title={High Probability Bounds for Bandit Stochastic and Adversarial Strongly Convex Optimization},
  author={Mahdavi, Mehrdad and Jin, Rong},
  year={2012}
}




@inproceedings{mahdavi2013multi,
  title={Stochastic Convex Optimization with Multiple Objectives},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  booktitle={Advances in Neural Information Processing Systems 26 (NIPS)},
  year={2013}
}


@inproceedings{mahdavi2013condition,
  title={Linear Convergence with Condition Number Independent Access of Full Gradients},
  author={Zhang, Lijun and Mahdavi, Mehrdad and Jin, Rong},
  booktitle={Advances in Neural Information Processing Systems 26 (NIPS)},
  year={2013}
}


@inproceedings{mahdavi2013mixedgrad,
  title={Mixed Optimization for Smooth Functions},
  author={Mahdavi, Mehrdad and Zhang, Lijun and Jin, Rong},
  booktitle={Advances in Neural Information Processing Systems 26 (NIPS)},
  year={2013}
}

@article{jin2012improved,
  title={Improved Bounds for the Nystrom Method with Application to Kernel Classification},
  author={Jin, Rong and Yang, Tianbao and Mahdavi, Mehrdad and Li, Y and Zhou, Z},
  year={2013},
  journal={IEEE Transaction on Information Theory},
  publisher={IEEE}
}

@article{yang2013regret,
  title={Regret bounded by gradual variation for online convex optimization},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Zhu, Shenghuo},
  journal={Machine Learning},
  pages={1--41},
  year={2013},
  publisher={Springer US}
}

@article{wang2018cooperative,
  title={Cooperative SGD: A unified framework for the design and analysis of communication-efficient SGD algorithms},
  author={Wang, Jianyu and Joshi, Gauri},
  journal={arXiv preprint arXiv:1808.07576},
  year={2018}
}
@inproceedings{haddadpour2018cross,
  title={Cross-iteration coded computing},
  author={Haddadpour, Farzin and Yang, Yaoqing and Cadambe, Viveck and Grover, Pulkit},
  booktitle={2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)},
  pages={196--203},
  year={2018},
  organization={IEEE}
}



@inproceedings{mcdonald2009efficient,
  title={Efficient large-scale distributed training of conditional maximum entropy models},
  author={Mcdonald, Ryan and Mohri, Mehryar and Silberman, Nathan and Walker, Dan and Mann, Gideon S},
  booktitle={Advances in Neural Information Processing Systems},
  pages={1231--1239},
  year={2009}
}

@inproceedings{zinkevich2010parallelized,
  title={Parallelized stochastic gradient descent},
  author={Zinkevich, Martin and Weimer, Markus and Li, Lihong and Smola, Alex J},
  booktitle={Advances in neural information processing systems},
  pages={2595--2603},
  year={2010}
}

@inproceedings{zhang2012communication,
  title={Communication-efficient algorithms for statistical optimization},
  author={Zhang, Yuchen and Wainwright, Martin J and Duchi, John C},
  booktitle={Advances in Neural Information Processing Systems},
  pages={1502--1510},
  year={2012}
}

@article{mcwilliams2014loco,
  title={LOCO: Distributing ridge regression with random projections},
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  number    = {3},
  pages     = {369--406},
  year      = {2015}
}
@inproceedings{johnson2013accelerating,
  title={Accelerating stochastic gradient descent using predictive variance reduction},
  author={Johnson, Rie and Zhang, Tong},
  booktitle={Advances in Neural Information Processing Systems},
  pages={315--323},
  year={2013}
}
@article{mahdavi2014exploiting,
  title={Exploiting Smoothness in Statistical Learning, Sequential Prediction, and Stochastic Optimization},
  author={Mahdavi, Mehrdad},
  journal={P.h.D Thesis},
  year={2014}
}
@inproceedings{mahdavi2015lower,
  title={Lower and upper bounds on the generalization of stochastic exponentially concave optimization},
  author={Mahdavi, Mehrdad and Zhang, Lijun and Jin, Rong},
  booktitle={COLT},
  pages={1305--1320},
  year={2015}
}
@inproceedings{meshi2015smooth,
  title={Smooth and Strong: MAP Inference with Linear Convergence},
  author={Meshi, Ofer and Mahdavi, Mehrdad and Schwing, Alex},
  booktitle={Advances in Neural Information Processing Systems (NIPS)},
  pages={298--306},
  year={2015}
}
@inproceedings{meshi2016train,
  title={Train and Test Tightness of LP Relaxations in Structured Prediction},
  author={Meshi, Ofer and Mahdavi, Mehrdad and Weller, Adrian and Sontag, David},
  booktitle={Proceedings of The 33rd International Conference on Machine Learning (ICML)},
  year={2016}
}
@article{wang2016sketching,
  title={Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data},
  author={Wang, Jialei and Lee, Jason D and Mahdavi, Mehrdad and Kolar, Mladen and Srebro, Nathan},
  journal={arXiv preprint arXiv:1610.03045},
  year={2016}
}
@article{zhang2014random,
  title={Random Projections for Classification: A Recovery Approach},
  author={Zhang, Lijun and Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao and Zhu, Shenghuo},
  journal={IEEE transactions on Infromation Theory},
  volume={60},
  number={11},
  year={2014}
}
@article{forsati2014matrix,
  title={Matrix Factorization with Explicit Trust and Distrust Side Information for Improved Social Recommendation},
  author={Forsati, Rana and Mahdavi, Mehrdad and Shamsfard, Mehrnoush and Sarwat, Mohamed},
  journal={ACM Transactions on Information Systems (TOIS)},
  volume={32},
  number={4},
  pages={17},
  year={2014},
  publisher={ACM}
}
@article{chandrasekaran2013computational,
  title={Computational and statistical tradeoffs via convex relaxation},
  author={Chandrasekaran, Venkat and Jordan, Michael I},
  journal={Proceedings of the National Academy of Sciences},
  volume={110},
  number={13},
  pages={E1181--E1190},
  year={2013},
  publisher={National Acad Sciences}
}

@article{omran2008global,
  title={Global-best harmony search},
  author={Omran, Mahamed  and Mahdavi, Mehrdad},
  journal={Applied Mathematics and Computation},
  volume={198},
  number={2},
  pages={643--656},
  year={2008},
  publisher={Elsevier}
}

@article{mahdavi2007improved,
  title={An improved harmony search algorithm for solving optimization problems},
  author={Mahdavi, Mehrdad and Fesanghary, Mohammad and Damangir, E},
  journal={Applied Mathematics and Computation},
  volume={188},
  number={2},
  pages={1567--1579},
  year={2007},
  publisher={Elsevier}
}


@article{omran2008global,
  title={Global-best harmony search},
  author={Omran, Mahamed  and Mahdavi, Mehrdad},
  journal={Applied Mathematics and Computation},
  volume={198},
  number={2},
  pages={643--656},
  year={2008},
  publisher={Elsevier}
}



@article{mahdavi2009harmony,
  title={Harmony K-means algorithm for document clustering},
  author={Mahdavi, Mehrdad and Abolhassani, Hassan},
  journal={Data Mining and Knowledge Discovery},
  volume={18},
  number={3},
  pages={370--391},
  year={2009},
  publisher={Springer}
}

@inproceedings{williams2001using,
  title={Using the Nystr{\"o}m method to speed up kernel machines},
  author={Williams, Christopher and Seeger, Matthias},
  booktitle={Advances in Neural Information Processing Systems 13},
  year={2001},
  organization={Citeseer}
}

@book{nesterov2004introductory,
  title={Introductory lectures on convex optimization: A basic course},
  author={Nesterov, Yurii},
  volume={87},
  year={2004},
  publisher={Springer}
}

@book{scholkopf2002learning,
  title={Learning with kernels},
  author={Sch{\"o}lkopf, Bernhard and Smola, Alexander J},
  year={2002},
  publisher={âTheâ MIT Press}
}

@book{national2013Frontiers,
  title={Frontiers in Massive Data Analysis},
  author={Committee on the Analysis of Massive Data; Committee on Applied and Theoretical Statistics; Board on Mathematical Sciences and Their Applications; Division on Engineering and Physical Sciences; National Research Council},
  isbn={9780309287784},
  url={http://www.nap.edu/openbook.php?record_id=18374},
  year={2013},
  publisher={The National Academies Press}
}

@article{mahdavi2007improved,
  title={An Improved Harmony Search Algorithm for Solving Optimization Problems},
  author={Mahdavi, Mehrdad and Fesanghary, M and Damangir, E},
  journal={Applied Mathematics and Computation},
  volume={188},
  number={2},
  pages={1567--1579},
  year={2007},
  publisher={Elsevier}
}

@article{omran2008global,
  title={Global-best harmony search},
  author={Omran, Mahamed GH and Mahdavi, Mehrdad},
  journal={Applied Mathematics and Computation},
  volume={198},
  number={2},
  pages={643--656},
  year={2008},
  publisher={Elsevier}
}

@article{forsati2008harmony,
  title={Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing},
  author={Forsati, R and Haghighat, AT and Mahdavi, M},
  journal={Computer Communications},
  volume={31},
  number={10},
  pages={2505--2519},
  year={2008},
  publisher={Elsevier}
}

@article{mahdavi2009harmony,
  title={Harmony K-means algorithm for document clustering},
  author={Mahdavi, Mehrdad and Abolhassani, Hassan},
  journal={Data Mining and Knowledge Discovery},
  volume={18},
  number={3},
  pages={370--391},
  year={2009},
  publisher={Springer US}
}

@article{mahdavi2008novel,
  title={Novel meta-heuristic algorithms for clustering web documents},
  author={Mahdavi, Mehrdad and Chehreghani, M Haghir and Abolhassani, Hassan and Forsati, Rana},
  journal={Applied Mathematics and Computation},
  volume={201},
  number={1},
  pages={441--451},
  year={2008},
  publisher={Elsevier}
}

@inproceedings{forsati2008efficient,
  title={An efficient algorithm for bandwidth-delay constrained least cost multicast routing},
  author={Forsati, Rana and Mahdavi, Mehrdad and Haghighat, Abolfazl Torghy and Ghariniyat, A},
  booktitle={Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on},
  pages={001641--001646},
  year={2008},
  organization={IEEE}
}

@inproceedings{forsati2009effective,
  title={Effective page recommendation algorithms based on distributed learning automata},
  author={Forsati, Rana and Rahbar, Afsaneh and Mahdavi, Mehrdad},
  booktitle={Computing in the Global Information Technology, 2009. ICCGI'09. Fourth International Multi-Conference on},
  pages={41--46},
  year={2009},
  organization={IEEE}
}

@incollection{mahdavi2009bandwidth,
  title={Bandwidth-Delay Constrained Least Cost Multicast Routing for Multimedia Communication},
  author={Mahdavi, Mehrdad and Forsati, Rana and Movaghar, Ali},
  booktitle={Advances in Computer Science and Engineering},
  pages={737--740},
  year={2009},
  publisher={Springer Berlin Heidelberg}
}

@article{khodamoradi2007upper,
  title={Upper Bounding the Price of Anarchy in Atomic Splittable Selfish Routing},
  author={Khodamoradi, Kamyar and Mahdavi, Mehrdad and Ghodsi, Mohammad},
  year={2007}
}

@incollection{mahdavi2009solving,
  title={Solving NP-Complete Problems by Harmony Search},
  author={Mahdavi, Mehrdad},
  booktitle={Music-Inspired Harmony Search Algorithm},
  pages={53--70},
  year={2009},
  publisher={Springer Berlin Heidelberg}
}

@article{yang2011regret,
  title={Regret Bound by Variation for Online Convex Optimization},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Zhu, Shenghuo},
  journal={Arxiv preprint arXiv:1111.6337},
  year={2011}
}

@article{mahdavi2011trading,
  title={Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints},
  author={Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  journal={Arxiv preprint arXiv:1111.6082},
  year={2011}
}


@article{forsati2007web,
  title={Web page personalization based on distributed learning automata},
  author={Forsati, R and Meybodi, MR and Mahdavi, M},
  journal={Proc. IKT, Ferdowsi University of Mashad, Mashad, Iran},
  year={2007}
}

@article{mahdavi2012efficient,
  title={Efficient constrained regret minimization},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  journal={arXiv preprint arXiv:1205.2265},
  year={2012}
}

@article{yang2012multiple,
  title={Multiple Kernel Learning from Noisy Labels by Stochastic Programming},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Zhang, Lijun and Zhou, Yang},
  journal={ICML},
  year={2012}
}

@inproceedings{chiang2012online,
  title={Online Optimization with Gradual Variations.},
  author={Yang, Tianbao  and Mahdavi, Mehrdad and  Jin, Rong and Zhu, Shenghuo},
  booktitle={Conference on Learning Theory (COLT)},
  year={2012}
}

@inproceedings{yang2012online,
  title={Online Kernel Selection: Algorithms and Evaluations.},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Yi, Jinfeng and Hoi, Steven CH},
  booktitle={AAAI},
  year={2012}
}

@article{forsati2012efficient,
  title={Efficient stochastic algorithms for document clustering},
  author={Forsati, Rana and Mahdavi, Mehrdad and Shamsfard, Mehrnoosh and Reza Meybodi, Mohammad},
  journal={Information Sciences},
  year={2012},
  publisher={Elsevier}
}

@article{fesanghary2008hybridizing,
  title={Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems},
  author={Fesanghary, M and Mahdavi, M and Minary-Jolandan, M and Alizadeh, Y},
  journal={Computer methods in applied mechanics and engineering},
  volume={197},
  number={33},
  pages={3080--3091},
  year={2008},
  publisher={North-Holland}
}

@inproceedings{forsati2008web,
  title={Web page clustering using harmony search optimization},
  author={Forsati, Rana and Mahdavi, Mehrdad and Kangavari, Mohammadreza and Safarkhani, Banafsheh},
  booktitle={Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on},
  pages={001601--001604},
  year={2008},
  organization={IEEE}
}

@inproceedings{forsati2008hybridization,
  title={Hybridization of K-means and harmony search methods for web page clustering},
  author={Forsati, Rana and Meybodi, Mohammad Reza and Mahdavi, Mehrdad and Neiat, Azadeh Ghari},
  booktitle={Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT'08. IEEE/WIC/ACM International Conference on},
  volume={1},
  pages={329--335},
  year={2008},
  organization={IEEE}
}

@incollection{forsati2010web,
  title={Web text mining using harmony search},
  author={Forsati, Rana and Mahdavi, Mehrdad},
  booktitle={Recent advances in harmony search algorithm},
  pages={51--64},
  year={2010},
  publisher={Springer Berlin Heidelberg}
}

@article{mahdavi2012improved,
  title={An Improved Bound for the Nystrom Method for Large Eigengap},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  journal={arXiv preprint arXiv:1209.0001},
  year={2012}
}

@inproceedings{yi2012robust,
  title={Robust Ensemble Clustering by Matrix Completion},
  author={Yi, Jinfeng and Yang, Tianbao and Jin, Rong and Jain, Anil K and Mahdavi, Mehrdad},
  booktitle={ICDM},
  year={2012},
  organization={IEEE}
}

@inproceedings{yang2012nystrom,
  title={Nystrom Method vs Random Fourier Features: A Theoretical and Empirical Comparison},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Li, Yu-Feng and Jin, Rong and Zhou, Zhi-Hua},
  year={2012},
  booktitle={Advances in Neural Information Processing Systems 25 (NIPS)},
}

@inproceedings{mahdavi2012online,
  title={Online Decision Making under Stochastic Constraints},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  booktitle={Discrete Optimization in Machine Learning (DISCML), NIPS 2012 Workshop},
  year={2012}
}

@article{mahdavi2012trading,
  title={Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints},
  author={Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  journal={Journal of Machine Learning Research (JMLR)},
  volume={13},
  pages={2503--2528},
  year={2012},
  publisher={MIT Press}
}

@inproceedings{mahdavi2012stochastic,
  title={Stochastic Gradient Descent with Only One Projection},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong and Zhu, Shenghuo and Yi, Jinfeng},
  booktitle={Advances in Neural Information Processing Systems 25 (NIPS)},
  year={2012}
}

@article{mahdavi2012online,
  title={Online Stochastic Optimization with Multiple Objectives},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  journal={arXiv preprint arXiv:1211.6013},
  year={2012}
}


@article{jin2013sparse,
  title={Sparse Multiple Kernel Learning with Geometric Convergence Rate},
  author={Jin, Rong and Yang, Tianbao and Mahdavi, Mehrdad},
  journal={arXiv preprint arXiv:1302.0315},
  year={2013}
}


@inproceedings{zhang2013recovering,
  title={Recovering the Optimal Solution by Dual Random Projection},
  author={Zhang, Lijun and Mahdavi, Mehrdad and Jin, Rong and Yang, Tianbao},
  booktitle={Conference on Learning Theory (COLT)},
  year={2013}
}


@inproceedings{mahdavi2013passive,
  title={Passive Learning with Target Risk},
  author={Mahdavi, Mehrdad and Jin, Rong},
  booktitle={Conference on Learning Theory (COLT)},
  year={2013}
}

@article{mahdavi2012high,
  title={High Probability Bounds for Bandit Stochastic and Adversarial Strongly Convex Optimization},
  author={Mahdavi, Mehrdad and Jin, Rong},
  year={2012}
}




@inproceedings{mahdavi2013multi,
  title={Stochastic Convex Optimization with Multiple Objectives},
  author={Mahdavi, Mehrdad and Yang, Tianbao and Jin, Rong},
  booktitle={Advances in Neural Information Processing Systems 26 (NIPS)},
  year={2013}
}


@inproceedings{mahdavi2013condition,
  title={Linear Convergence with Condition Number Independent Access of Full Gradients},
  author={Zhang, Lijun and Mahdavi, Mehrdad and Jin, Rong},
  booktitle={Advances in Neural Information Processing Systems 26 (NIPS)},
  year={2013}
}


@inproceedings{mahdavi2013mixedgrad,
  title={Mixed Optimization for Smooth Functions},
  author={Mahdavi, Mehrdad and Zhang, Lijun and Jin, Rong},
  booktitle={Advances in Neural Information Processing Systems 26 (NIPS)},
  year={2013}
}

@article{jin2012improved,
  title={Improved Bounds for the Nystrom Method with Application to Kernel Classification},
  author={Jin, Rong and Yang, Tianbao and Mahdavi, Mehrdad and Li, Y and Zhou, Z},
  year={2013},
  journal={IEEE Transaction on Information Theory},
  publisher={IEEE}
}

@article{yang2013regret,
  title={Regret bounded by gradual variation for online convex optimization},
  author={Yang, Tianbao and Mahdavi, Mehrdad and Jin, Rong and Zhu, Shenghuo},
  journal={Machine Learning},
  pages={1--41},
  year={2013},
  publisher={Springer US}
}


@inproceedings{haddadpour2018cross,
  title={Cross-iteration coded computing},
  author={Haddadpour, Farzin and Yang, Yaoqing and Cadambe, Viveck and Grover, Pulkit},
  booktitle={2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)},
  pages={196--203},
  year={2018},
  organization={IEEE}
}

@inproceedings{mcdonald2009efficient,
  title={Efficient large-scale distributed training of conditional maximum entropy models},
  author={Mcdonald, Ryan and Mohri, Mehryar and Silberman, Nathan and Walker, Dan and Mann, Gideon S},
  booktitle={Advances in Neural Information Processing Systems},
  pages={1231--1239},
  year={2009}
}

@inproceedings{zinkevich2010parallelized,
  title={Parallelized stochastic gradient descent},
  author={Zinkevich, Martin and Weimer, Markus and Li, Lihong and Smola, Alex J},
  booktitle={Advances in neural information processing systems},
  pages={2595--2603},
  year={2010}
}

@inproceedings{zhang2012communication,
  title={Communication-efficient algorithms for statistical optimization},
  author={Zhang, Yuchen and Wainwright, Martin J and Duchi, John C},
  booktitle={Advances in Neural Information Processing Systems},
  pages={1502--1510},
  year={2012}
}

@article{mcwilliams2014loco,
  title={LOCO: Distributing ridge regression with random projections},
  author={McWilliams, Brian and Heinze, Christina and Meinshausen, Nicolai and Krummenacher, Gabriel and Vanchinathan, Hastagiri P},
  journal={stat},
  volume={1050},
  pages={26},
  year={2014},
  publisher={Citeseer}
}

@inproceedings{heinze2016dual,
  title={Dual-loco: Distributing statistical estimation using random projections},
  author={Heinze, Christina and McWilliams, Brian and Meinshausen, Nicolai},
  booktitle={Artificial Intelligence and Statistics},
  pages={875--883},
  year={2016}
}

@inproceedings{shamir2014communication,
  title={Communication-efficient distributed optimization using an approximate newton-type method},
  author={Shamir, Ohad and Srebro, Nati and Zhang, Tong},
  booktitle={International conference on machine learning},
  pages={1000--1008},
  year={2014}
}

@inproceedings{balcan2012distributed,
  title={Distributed learning, communication complexity and privacy},
  author={Balcan, Maria Florina and Blum, Avrim and Fine, Shai and Mansour, Yishay},
  booktitle={Conference on Learning Theory},
  pages={26--1},
  year={2012}
}

@inproceedings{arjevani2015communication,
  title={Communication complexity of distributed convex learning and optimization},
  author={Arjevani, Yossi and Shamir, Ohad},
  booktitle={Advances in neural information processing systems},
  pages={1756--1764},
  year={2015}
}

@article{lee2017distributed,
  title={Distributed stochastic variance reduced gradient methods by sampling extra data with replacement},
  author={Lee, Jason D and Lin, Qihang and Ma, Tengyu and Yang, Tianbao},
  journal={The Journal of Machine Learning Research},
  volume={18},
  number={1},
  pages={4404--4446},
  year={2017},
  publisher={JMLR. org}
}
@inproceedings{kang2009pegasus,
  title={Pegasus: A peta-scale graph mining system implementation and observations},
  author={Kang, U and Tsourakakis, Charalampos E and Faloutsos, Christos},
  booktitle={Data Mining, 2009. ICDM'09. Ninth IEEE International Conference on},
  pages={229--238},
  year={2009},
  organization={IEEE}
}
@article{gleich2004fast,
  title={Fast parallel PageRank: A linear system approach},
  author={Gleich, David and Zhukov, Leonid and Berkhin, Pavel},
  journal={Yahoo! Research Technical Report YRL-2004-038, available via http://research. yahoo. com/publication/YRL-2004-038. pdf},
  volume={13},
  pages={22},
  year={2004}
}

@article{yin2017gradient,
  title={Gradient diversity: a key ingredient for scalable distributed learning},
  author={Yin, Dong and Pananjady, Ashwin and Lam, Max and Papailiopoulos, Dimitris and Ramchandran, Kannan and Bartlett, Peter},
  journal={arXiv preprint arXiv:1706.05699},
  year={2017}
}

@inproceedings{zhang2015disco,
  title={DiSCO: Distributed optimization for self-concordant empirical loss},
  author={Zhang, Yuchen and Lin, Xiao},
  booktitle={International conference on machine learning},
  pages={362--370},
  year={2015}
}

@article{ma2015adding,
  title={Adding vs. averaging in distributed primal-dual optimization},
  author={Ma, Chenxin and Smith, Virginia and Jaggi, Martin and Jordan, Michael I and Richt{\'a}rik, Peter and Tak{\'a}{\v{c}}, Martin},
  journal={arXiv preprint arXiv:1502.03508},
  year={2015}
}

@book{nesterov2013introductory,
  title={Introductory lectures on convex optimization: A basic course},
  author={Nesterov, Yurii},
  volume={87},
  year={2013},
  publisher={Springer Science \& Business Media}
}

@inproceedings{demmel2008avoiding,
  title={Avoiding communication in sparse matrix computations},
  author={Demmel, James and Hoemmen, Mark and Mohiyuddin, Marghoob and Yelick, Katherine},
  booktitle={Parallel and Distributed Processing, 2008. IPDPS 2008. IEEE International Symposium on},
  pages={1--12},
  year={2008},
  organization={IEEE}
}

@article{demmel2012communication,
  title={Communication-optimal parallel and sequential QR and LU factorizations},
  author={Demmel, James and Grigori, Laura and Hoemmen, Mark and Langou, Julien},
  journal={SIAM Journal on Scientific Computing},
  volume={34},
  number={1},
  pages={A206--A239},
  year={2012},
  publisher={SIAM}
}

@inproceedings{wicky2017communication,
  title={Communication-avoiding parallel algorithms for solving triangular systems of linear equations},
  author={Wicky, Tobias and Solomonik, Edgar and Hoefler, Torsten},
  booktitle={Parallel and Distributed Processing Symposium (IPDPS), 2017 IEEE International},
  pages={678--687},
  year={2017},
  organization={IEEE}
}

@inproceedings{lipshitz2012communication,
  title={Communication-avoiding parallel strassen: Implementation and performance},
  author={Lipshitz, Benjamin and Ballard, Grey and Demmel, James and Schwartz, Oded},
  booktitle={Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis},
  pages={101},
  year={2012},
  organization={IEEE Computer Society Press}
}


@ARTICLE{PolyLin,
   author = {{Haddadpour}, F. and {Yang}, Y. and {Chaudhari}, M. and {Cadambe}, V.~R and 
	{Grover}, P.},
    title = "{Straggler-Resilient and Communication-Efficient Distributed Iterative Linear Solver}",
  journal = {ArXiv e-prints},
   note = {1806.06140},
     year = 2018,
    month = jun,
}

@article{dean2013tail,
  title={The tail at scale},
  author={Dean, Jeffrey and Barroso, Luiz Andr{\'e}},
  journal={Communications of the ACM},
  volume={56},
  number={2},
  pages={74--80},
  year={2013},
  publisher={ACM}
}

@inproceedings{li2015coded,
  title={Coded mapreduce},
  author={Li, Songze and Maddah-Ali, Mohammad Ali and Avestimehr, A Salman},
  booktitle={Communication, Control, and Computing (Allerton), 2015 53rd Annual Allerton Conference on},
  pages={964--971},
  year={2015},
  organization={IEEE}
}


@inproceedings{li2016fundamental,
  title={Fundamental tradeoff between computation and communication in distributed computing},
  author={Li, Songze and Maddah-Ali, Mohammad Ali and Avestimehr, A Salman},
  booktitle={Information Theory (ISIT), 2016 IEEE International Symposium on},
  pages={1814--1818},
  year={2016},
  organization={IEEE}
}



@article{wang2018adaptive,
  title={Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD},
  author={Wang, Jianyu and Joshi, Gauri},
  journal={arXiv preprint arXiv:1810.08313},
  year={2018}
}

@inproceedings{lin2019don,
  author    = {Tao Lin and
               Sebastian U. Stich and
               Kumar Kshitij Patel and
               Martin Jaggi},
  title     = {Don't Use Large Mini-batches, Use Local {SGD}},
  booktitle = {Proceedings of the 8th International Conference on Learning Representations (ICLR)},
  address   = {Addis Ababa, Ethiopia},
  year      = {2020}
}



@inproceedings{bonawitz2017practical,
  author    = {Keith Bonawitz and
               Vladimir Ivanov and
               Ben Kreuter and
               Antonio Marcedone and
               H. Brendan McMahan and
               Sarvar Patel and
               Daniel Ramage and
               Aaron Segal and
               Karn Seth},
  title     = {Practical Secure Aggregation for Privacy-Preserving Machine Learning},
  booktitle = {Proceedings of the 2017 {ACM} {SIGSAC} Conference on Computer and
               Communications Security (CCS)},
  address = {Dallas, TX},
  pages     = {1175--1191},
  year      = {2017}
}


@inproceedings{duchi2013local,
  title={Local privacy and statistical minimax rates},
  author={Duchi, John C and Jordan, Michael I and Wainwright, Martin J},
  booktitle={2013 IEEE 54th Annual Symposium on Foundations of Computer Science},
  pages={429--438},
  year={2013},
  organization={IEEE}
}

@inproceedings{alistarh2018convergence,
  title={The convergence of sparsified gradient methods},
  author={Alistarh, Dan and Hoefler, Torsten and Johansson, Mikael and Konstantinov, Nikola and Khirirat, Sarit and Renggli, C{\'e}dric},
  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
  pages={5973--5983},
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  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address = {virtual},
  pages     = {19680--19691},
  year      = {2021}
}

@inproceedings{zhang2021graph,
  author    = {Shijie Zhang and
               Hongzhi Yin and
               Tong Chen and
               Zi Huang and
               Lizhen Cui and
               Xiangliang Zhang},
  title     = {Graph Embedding for Recommendation against Attribute Inference Attacks},
  booktitle = {Proceedings of the Web Conference (WWW)},
  address = {Virtual Event / Ljubljana, Slovenia},
  pages     = {3002--3014},
  year      = {2021}
}

@inproceedings{beigi2020privacy,
  author    = {Ghazaleh Beigi and
               Ahmadreza Mosallanezhad and
               Ruocheng Guo and
               Hamidreza Alvari and
               Alexander Nou and
               Huan Liu},
  title     = {Privacy-Aware Recommendation with Private-Attribute Protection using
               Adversarial Learning},
  booktitle = {Proceedings of the Thirteenth {ACM} International Conference on Web Search
               and Data Mining (WSDM)},
  address = {Houston, TX, USA},
  pages     = {34--42},
  year      = {2020}
}

@inproceedings{fang2023improved,
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  booktitle = {Proceedings of the Eleventh International Conference on Learning Representations (ICLR)}, 
  address   = {Kigali, Rwanda},
  year      = {2023}
}

@article{zhang2012functional,
  author    = {Jun Zhang and
               Zhenjie Zhang and
               Xiaokui Xiao and
               Yin Yang and
               Marianne Winslett},
  title     = {Functional Mechanism: Regression Analysis under Differential Privacy},
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@inproceedings{mironov2017renyi,
  author    = {Ilya Mironov},
  title     = {R{\'{e}}nyi Differential Privacy},
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}

@article{dong2022gaussian,
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  journal={Journal of the Royal Statistical Society Series B: Statistical Methodology},
  volume={84},
  number={1},
  pages={3--37},
  year={2022},
  publisher={Oxford University Press}
}

@inproceedings{jayaraman2019evaluating,
  author    = {Bargav Jayaraman and
               David Evans},
  title     = {Evaluating Differentially Private Machine Learning in Practice},
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  address = {Santa Clara,
               CA},
  pages     = {1895--1912},
  year      = {2019}
}

@article{comas2017individual,
  author    = {Jordi Soria{-}Comas and
               Josep Domingo{-}Ferrer and
               David S{\'{a}}nchez and
               David Meg{\'{\i}}as},
  title     = {Individual Differential Privacy: {A} Utility-Preserving Formulation
               of Differential Privacy Guarantees},
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@article{desfontaines2020sok,
  author    = {Damien Desfontaines and
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  number    = {2},
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  year      = {2020}
}

@inproceedings{nissim2007smooth,
  author       = {Kobbi Nissim and
                  Sofya Raskhodnikova and
                  Adam D. Smith},
  title        = {Smooth sensitivity and sampling in private data analysis},
  booktitle    = {Proceedings of the 39th Annual {ACM} Symposium on Theory of Computing (STOC)},
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@misc{Fledge2021 ,
year = "2021",
author = "WICG",
title = "First Experiment (FLEDGE)",
url = "https://github.com/WICG/turtledove/blob/main/FLEDGE.md"
 }
 


@misc{FLoC2020 ,
author = "Google Research \& Ads",
year = "2020",
title = "Computing k-anonymity for a dataset",
url = "https://cloud.google.com/dlp/docs/compute-k-anonymity"
 }
 
 @misc{FLoC2020cohort ,
author = "Google Research \& Ads",
year = "2020",
title = "Evaluation of cohort algorithms for the FLoC API",
url = "https://github.com/google/ads-privacy/blob/master/proposals/FLoC/FLOC-Whitepaper-Google.pdf"
 }

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  pages={557--570},
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  year={2007}
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@inproceedings{li2022signrff,
  author    = {Xiaoyun Li and
               Ping Li},
  title     = {{SignRFF}: Sign Random Fourier Features},
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@misc{Fledge2023K ,
author = "Google Chrome",
year = "2023",
title = "Status of pending FLEDGE capabilities",
url = "https://developer.chrome.com/docs/privacy-sandbox/fledge-api/feature-status/"
 }

 @inproceedings{ravichandran2005randomized,
  author    = {Deepak Ravichandran and
               Patrick Pantel and
               Eduard H. Hovy},
  title     = {Randomized Algorithms and {NLP:} Using Locality Sensitive Hash Functions
               for High Speed Noun Clustering},
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address ={University
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@misc{att2021,
  title = {App Tracking Transparency},
  year = "2021",
  author = "Apple Inc.",
  url = "https://developer.apple.com/documentation/apptrackingtransparency",
  note = {Accessed: 2023-04-19}
}

@misc{sandbox2023,
  title = {The Privacy Sandbox Beta is coming to Android},
  year = "2023",
  author = "Google Inc.",
  url = "https://blog.google/products/android/the-privacy-sandbox-beta-is-coming-to-android/",
  note = {Accessed: 2023-04-19}
}

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}



@inproceedings{dautume2019episodic,
  author       = {Cyprien de Masson d'Autume and
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                  Lingpeng Kong and
                  Dani Yogatama},
  title        = {Episodic Memory in Lifelong Language Learning},
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  year         = {2019}
}

@inproceedings{madotto2021continual,
  author       = {Andrea Madotto and
                  Zhaojiang Lin and
                  Zhenpeng Zhou and
                  Seungwhan Moon and
                  Paul A. Crook and
                  Bing Liu and
                  Zhou Yu and
                  Eunjoon Cho and
                  Pascale Fung and
                  Zhiguang Wang},
  title        = {Continual Learning in Task-Oriented Dialogue Systems},
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@inproceedings{liu2020learning,
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  year         = {2020}
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  title        = {Sentence Embedding Alignment for Lifelong Relation Extraction},
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  year         = {2019}
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@inproceedings{shen2018deep,
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                  Zachary C. Lipton and
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                  Animashree Anandkumar},
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  year         = {2018}
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               Alan L. Yuille and
               Quoc V. Le},
  title     = {Adversarial Examples Improve Image Recognition},
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@inproceedings{yang2022continual,
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  address      = {Abu Dhabi, United Arab Emirates},
  pages        = {158--170},
  year         = {2022}
}

@inproceedings{lewis2020bart,
  author       = {Mike Lewis and
                  Yinhan Liu and
                  Naman Goyal and
                  Marjan Ghazvininejad and
                  Abdelrahman Mohamed and
                  Omer Levy and
                  Veselin Stoyanov and
                  Luke Zettlemoyer},
  title        = {{BART:} Denoising Sequence-to-Sequence Pre-training for Natural Language
                  Generation, Translation, and Comprehension},
  booktitle    = {Proceedings of the 58th Annual Meeting of the Association for Computational
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  year         = {2020}
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@inproceedings{li2022lpc,
  author       = {Xiaodi Li and
                  Zhuoyi Wang and
                  Dingcheng Li and
                  Latifur Khan and
                  Bhavani Thuraisingham},
  title        = {{LPC:} {A} Logits and Parameter Calibration Framework for Continual
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  booktitle    = {Findings of the Association for Computational Linguistics (EMNLP)},
  address     = {Abu Dhabi, United Arab Emirates},
  pages        = {7142--7155},
  year         = {2022}
}

@inproceedings{li2022overcoming,
  author       = {Dingcheng Li and
                  Zheng Chen and
                  Eunah Cho and
                  Jie Hao and
                  Xiaohu Liu and
                  Fan Xing and
                  Chenlei Guo and
                  Yang Liu},
  title        = {Overcoming Catastrophic Forgetting During Domain Adaptation of Seq2seq
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  booktitle    = {Proceedings of the 2022 Conference of the North American Chapter of
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  address      = {Seattle, WA},
  pages        = {5441--5454},
  year         = {2022}
}

@inproceedings{wang2019concept,
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                  Heyan Huang and
                  Yuxiang Zhou},
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  year         = {2019}
}

@inproceedings{dong2021parasci,
  author       = {Qingxiu Dong and
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  title        = {{ParaSCI}: {A} Large Scientific Paraphrase Dataset for Longer Paraphrase
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  booktitle    = {Proceedings of the 16th Conference of the European Chapter of the
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  year         = {2021}
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  year         = {2022}
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@inproceedings{yang2015bayesian,
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  author       = {Arnaud Berlioz and
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  pages        = {107--114},
  year         = {2015}
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  year         = {2018}
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  title        = {{XLNet}: Generalized Autoregressive Pretraining for Language Understanding},
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  pages        = {5754--5764},
  year         = {2019}
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  year         = {2017}
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  title        = {Placing search in context: the concept revisited},
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