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               Peng Yang and
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  title     = {Mitigating Forgetting in Online Continual Learning with Neuron Calibration},
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  year      = {2021}
}

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@inproceedings{shrivastava2014defense,
  author    = {Anshumali Shrivastava and
               Ping Li},
  title     = {In Defense of Minhash over Simhash},
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  pages     = {886--894},
  year      = {2014}
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@inproceedings{shrivastava2014densifying,
  author        = "Anshumali Shrivastava and Ping Li",
  title         = "Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search",
  booktitle     = "Proceedings of the 31th International Conference on Machine Learning (ICML)",
  address       = "Beijing, China",
  year          = "2014"
}

@inproceedings{li2014coding,
  author    = {Ping Li and
               Michael Mitzenmacher and
               Anshumali Shrivastava},
  title     = {Coding for Random Projections},
  booktitle = {Proceedings of the 31th International Conference on Machine Learning (ICML)},
  address   = {Beijing, China},
  pages     = {676--684},
  year      = {2014}
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@inproceedings{ioffe2010improved,
  author    = {Sergey Ioffe},
  title     = {Improved Consistent Sampling, Weighted Minhash and {L1} Sketching},
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               Sydney, Australia},
  pages     = {246--255},
  year      = {2010}
}

@inproceedings{shrivastava2014asymmetric,
  author    = {Anshumali Shrivastava and
               Ping Li},
  title     = {Asymmetric {LSH} {(ALSH)} for Sublinear Time Maximum Inner Product
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  booktitle = {Advances in Neural Information Processing Systems (NIPS)},
  address   = {Montreal,  Canada},
  pages     = {2321--2329},
  year      = {2014}
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@inproceedings{li2013sign,
  author    = {Ping Li and
               Gennady Samorodnitsky and
               John E. Hopcroft},
  title     = {Sign Cauchy Projections and Chi-Square Kernel},
  booktitle = {Advances in Neural Information Processing Systems (NIPS)},
  pages     = {2571--2579},
  year = {2013},
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@inproceedings{li20150,
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  booktitle = {Proceedings of the 21th {ACM} {SIGKDD} International Conference on
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  year = {2015},
  pages     = {665--674},
  address = {Sydney, Australia}
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@techreport{Report:Li_GMM16,
  author        = "Ping Li",
  title         = "Generalized Min-Max Kernel and Generalized Consistent Weighted Sampling",
  institution   = "arXiv:1605.05721",
  year          = "2016"
}

@techreport{Report:Li_GMM_Nys16,
  author        = "Ping Li",
  title         = "Nystrom Method for Approximating the GMM Kernel",
  institution   = "arXiv:1605.05721",
  year          = "2016"
}

@inproceedings{shrivastava2015asymmetric,
  author    = {Anshumali Shrivastava and
               Ping Li},
  title     = {Asymmetric Minwise Hashing for Indexing Binary Inner Products and
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  booktitle = {Proceedings of the 24th International Conference on World Wide Web (WWW)},
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  year      = {2015},
  address   = {Florence, Italy}
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@inproceedings{li2019random,
  author    = {Xiaoyun Li and
               Ping Li},
  title     = {Random Projections with Asymmetric Quantization},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {Vancouver, Canada},
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  year      = {2019}
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@inproceedings{shrivastava2016simple,
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  booktitle = {Neural Information Processing Systems (NIPS)},
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  year      = {2016}
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@inproceedings{li2017linearized,
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@inproceedings{yu2017greedy,
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@inproceedings{li2014core,
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@inproceedings{li2010approximating,
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@article{li2022pGMM,
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@inproceedings{li2007mcrank,
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@inproceedings{fei2021gemnn,
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               Jingyuan Zhang and
               Xingxuan Zhou and
               Junhao Zhao and
               Xinyang Qi and
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  address   = {Virtual Event, Canada},
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@inproceedings{zhao2020distributed,
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               Deping Xie and
               Ronglai Jia and
               Yulei Qian and
               Ruiquan Ding and
               Mingming Sun and
               Ping Li},
  title     = {Distributed Hierarchical {GPU} Parameter Server for Massive Scale
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  year      = {2020}
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@article{zhao2022communication_arxiv,
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@inproceedings{xu2021agile,
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               Xiaoyun Li and
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  title     = {Agile and Accurate {CTR} Prediction Model Training for Massive-Scale
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  year      = {2021}
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@inproceedings{wang2020improved,
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               Peng Yang and
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@inproceedings{yang2021robust,
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               Yingjie Lao and
               Ping Li},
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@article{li2022fast,
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@article{li2022package,
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@inproceedings{wang2022oie,
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               Minlong Peng and
               Mingming Sun and
               Ping Li},
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  address   = {Dublin, Ireland},
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  year      = {2022}
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               Michael Backes and
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               Michelle L. Mazurek and
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  title     = {You Get Where You're Looking for: The Impact of Information Sources
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@inproceedings{andow2019policylint,
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               Kapil Singh and
               Tao Xie},
  title     = {PolicyLint: Investigating Internal Privacy Policy Contradictions on
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@inproceedings{angeli2015leveraging,
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@inproceedings{banko2007open,
  author    = {Michele Banko and
               Michael J. Cafarella and
               Stephen Soderland and
               Matthew Broadhead and
               Oren Etzioni},
  editor    = {Manuela M. Veloso},
  title     = {Open Information Extraction from the Web},
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@inproceedings{beltramelli2018pix2code,
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  year      = {2018}
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@inproceedings{christensen2011analysis,
  author    = {Janara Christensen and
               Mausam and
               Stephen Soderland and
               Oren Etzioni},
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@inproceedings{cui2018neural,
  author    = {Lei Cui and
               Furu Wei and
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  address   = {Melbourne, Australia},
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  year      = {2018}
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@inproceedings{zimmeck2021privacyflash,
  author    = {Sebastian Zimmeck and
               Rafael Goldstein and
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  booktitle = {Proceedings of the 28th Annual Network and Distributed System Security Symposium (NDSS)},
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  year      = {2021}
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@inproceedings{del2013clausie,
  author    = {Luciano Del Corro and
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@inproceedings{etzioni2004web,
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               Doug Downey and
               Stanley Kok and
               Ana{-}Maria Popescu and
               Tal Shaked and
               Stephen Soderland and
               Daniel S. Weld and
               Alexander Yates},
  title     = {Web-scale information extraction in knowitall: (preliminary results)},
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@inproceedings{etzioni2011open,
  author    = {Oren Etzioni and
               Anthony Fader and
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  title     = {Open Information Extraction: The Second Generation},
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  address   = {Barcelona, Catalonia, Spain},
  pages     = {3--10},
  year      = {2011}
}





@inproceedings{fader2011identifying,
  author    = {Anthony Fader and
               Stephen Soderland and
               Oren Etzioni},
  title     = {Identifying Relations for Open Information Extraction},
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               Language Processing (EMNLP)},
  address   = {John McIntyre
               Conference Centre, Edinburgh, UK},
  pages     = {1535--1545},
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               Yang Liu and
               Jun Liu and
               Ting Liu},
  title     = {An Empirical Evaluation of {GDPR} Compliance Violations in Android
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@article{guaman2021gdpr,
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@article{hasan2021text2app,
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@article{kammuller2019designing,
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  title     = {{IMoJIE}: Iterative Memory-Based Joint Open Information Extraction},
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@inproceedings{li2018constructing,
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               Xiao Ding and
               Ting Liu},
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@article{lin2017program,
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@article{linden2020privacy,
  author    = {Thomas Linden and
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@article{liu2018survey,
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  year      = {2018}
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  author    = {Duc Cuong Nguyen and
               Dominik Wermke and
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               Michael Backes and
               Charles Weir and
               Sascha Fahl},
  title     = {A Stitch in Time: Supporting Android Developers in WritingSecure Code},
  booktitle = {Proceedings of the 2017 {ACM} {SIGSAC} Conference on Computer and
               Communications Security (CCS)},
  address   = {Dallas, TX},
  pages     = {1065--1077},
  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
               Online App Generators},
  booktitle = {Proceedings of the 2018 {IEEE} Symposium on Security and Privacy (SP)}, 
  address   = {San Francisco, CA},
  pages     = {634--647},
  year      = {2018}
}

@inproceedings{pal2016demonyms,
  author    = {Harinder Pal and
               Mausam},
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  year      = {2016}
}

@article{ro2020multi,
  author    = {Youngbin Ro and
               Yukyung Lee and
               Pilsung Kang},
  title     = {{Multi\({}^{\mbox{2}}\)OIE}: Multilingual Open Information Extraction
               based on Multi-Head Attention with {BERT}},
  booktitle = {Findings of the Association for Computational Linguistics: {EMNLP}},
  address   = {Online Event},
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  year      = {2020}
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@inproceedings{roy2019supervising,
  title={Supervising Unsupervised Open Information Extraction Models},
  author={Roy, Arpita and Park, Youngja and Lee, Taesung and Pan, Shimei},
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  pages={728--737},
  address = {Hong Kong, China},
  year={2019}
}

@inproceedings{saha2017bootstrapping,
  author    = {Swarnadeep Saha and
               Harinder Pal and
               Mausam},
  title     = {Bootstrapping for Numerical Open {IE}},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational
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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
               Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)},
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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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  address   = {San Diego, CA},
  year      = {2020}
}


@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
               Luke Zettlemoyer and
               Ido Dagan},
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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
               Xu Li and
               Xin Wang and
               Miao Fan and
               Yue Feng and
               Ping Li},
  title     = {Logician: {A} Unified End-to-End Neural Approach for Open-Domain Information
               Extraction},
  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}
}

@inproceedings{sun2020predicate,
  author    = {Mingming Sun and
               Wenyue Hua and
               Zoey Liu and
               Xin Wang and
               Kangjie Zheng and
               Ping Li},
  title     = {{A Predicate-Function-Argument Annotation of Natural Language for Open-Domain
               Information eXpression}},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural
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  year      = {2020}
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@inproceedings{tesfay2018read,
  author    = {Welderufael B. Tesfay and
               Peter Hofmann and
               Toru Nakamura and
               Shinsaku Kiyomoto and
               Jetzabel M. Serna},
  title     = {I Read but Don't Agree: Privacy Policy Benchmarking using Machine
               Learning and the {EU} {GDPR}},
  booktitle = {Companion of the The Web Conference 2018 on The Web Conference 2018 (WWW)},
  address   = {Lyon , France},
  pages     = {163--166},
  year      = {2018}
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@inproceedings{utz2019informed,
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               Martin Degeling and
               Sascha Fahl and
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  year      = {2019}
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               Steven M. Bellovin},
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@article{zimmeck2019maps,
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               N. Cameron Russell and
               Norman M. Sadeh},
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  author    = {Yossi Adi and
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               Benny Pinkas and
               Joseph Keshet},
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@inproceedings{zhang2022end,
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  year={2016}, 
  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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@inproceedings{sun2019lamol,
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@inproceedings{heo2019knowledge,
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  title     = {Knowledge Transfer via Distillation of Activation Boundaries Formed
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  booktitle = {Proceedings of the Thirty-Third {AAAI} Conference on Artificial Intelligence (AAAI)},
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  year      = {2019}
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@inproceedings{yoon2021online,
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@inproceedings{yin2020dreaming,
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               Jose M. Alvarez and
               Zhizhong Li and
               Arun Mallya and
               Derek Hoiem and
               Niraj K. Jha and
               Jan Kautz},
  title     = {Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion},
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  year={2021}
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@inproceedings{guo2020practical,
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               Cong Liu},
  title     = {Practical Poisoning Attacks on Neural Networks},
  booktitle = {Proceedings of the 16th European Conference on Computer Vision (ECCV), Part {XXVII} }, 
  address   = {Glasgow
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  year      = {2020}
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@inproceedings{chaudhry2018efficient,
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  year      = {2019}
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@article{aljundi2019gradient,
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  year      = {2019}
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               Yuqiao Chen and
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  title     = {{CLEAR:} Contrastive-Prototype Learning with Drift Estimation for
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  booktitle = {Proceedings of the Web Conference (WWW)}, 
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  year      = {2021}
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@inproceedings{wang2021cifdm,
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@inproceedings{killamsetty2020glister,
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@inproceedings{tan2019lxmert,
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@inproceedings{li2020unicoder,
  author    = {Gen Li and
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@inproceedings{chen2020uniter,
  author    = {Yen{-}Chun Chen and
               Linjie Li and
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               Ahmed El Kholy and
               Faisal Ahmed and
               Zhe Gan and
               Yu Cheng and
               Jingjing Liu},
  title     = {{UNITER:} UNiversal Image-TExt Representation Learning},
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@inproceedings{tan2020detecting,
  title     = {Detecting Cross-Modal Inconsistency to Defend against Neural Fake News},
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@inproceedings{su2020vl,
  author    = {Weijie Su and
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               Bin Li and
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  title     = {{VL-BERT:} Pre-training of Generic Visual-Linguistic Representations},
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  year      = {2020}
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@inproceedings{cho2020x,
  author    = {Jaemin Cho and 
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  year      = {2020}
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  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,
  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},
}

@inproceedings{ramesh2013audience,
  title = {{Audience segment expansion using distributed in-database k-means clustering}},
  author = {Ramesh, Archana and Teredesai, Ankur and Bindra, Ashish and Pokuri, Sreenivasulu and Uppala, Krishna},
  booktitle = {Proceedings of the Seventh International Workshop on Data Mining for Online Advertising},
  pages = {5},
  year = {2013},
  organization = {ACM},
}


@inproceedings{bindra2012distributed,
  title = {{Distributed big advertiser data mining}},
  author = {Bindra, Ashish and Pokuri, Srinivasulu and Uppala, Krishna and Teredesai, Ankur},
  booktitle = {Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on},
  pages = {914--914},
  year = {2012},
  organization = {IEEE},
}


@inproceedings{mangalampalli2011feature,
  title = {{A feature-pair-based associative classification approach to look-alike modeling for conversion-oriented user-targeting in tail campaigns}},
  author = {Mangalampalli, Ashish and Ratnaparkhi, Adwait and Hatch, Andrew O and Bagherjeiran, Abraham and Parekh, Rajesh and Pudi, Vikram},
  booktitle = {Proceedings of the 20th international conference companion on World wide web},
  pages = {85--86},
  year = {2011},
  organization = {ACM},
}


@inproceedings{bagherjeiran2010large,
  title = {{Large-scale customized models for advertisers}},
  author = {Bagherjeiran, Abraham and Hatch, Andrew and Ratnaparkhi, Adwait and Parekh, Rajesh},
  booktitle = {Data Mining Workshops (ICDMW), 2010 IEEE International Conference on},
  pages = {1029--1036},
  year = {2010},
  organization = {IEEE},
}


@inproceedings{kanagal2013focused,
  title = {{Focused matrix factorization for audience selection in display advertising}},
  author = {Kanagal, Bhargav and Ahmed, Amr and Pandey, Sandeep and Josifovski, Vanja and Garcia-Pueyo, Lluis and Yuan, Jeff},
  booktitle = {Data Engineering (ICDE), 2013 IEEE 29th International Conference on},
  pages = {386--397},
  year = {2013},
  organization = {IEEE},
}


@article{lecun2015deep,
  title = {{Deep learning}},
  author = {LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  journal = {Nature},
  volume = {521},
  number = {7553},
  pages = {436--444},
  year = {2015},
  publisher = {Nature Research},
}

@inproceedings{vincent2008extracting,
  title={Extracting and composing robust features with denoising autoencoders},
  author={Vincent, Pascal and Larochelle, Hugo and Bengio, Yoshua and Manzagol, Pierre-Antoine},
  booktitle={Proceedings of the 25th international conference on Machine learning},
  pages={1096--1103},
  year={2008},
  organization={ACM}
}


@inproceedings{salimans2016improved,
  title={Improved techniques for training gans},
  author={Salimans, Tim and Goodfellow, Ian and Zaremba, Wojciech and Cheung, Vicki and Radford, Alec and Chen, Xi},
  booktitle={Advances in Neural Information Processing Systems},
  pages={2234--2242},
  year={2016}
}

@inproceedings{ioffe2015batch,
  title={Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift},
  author={Ioffe, Sergey and Szegedy, Christian},
  booktitle={International Conference on Machine Learning},
  pages={448--456},
  year={2015}
}

@inproceedings{gulrajani2017improved,
  title={Improved training of Wasserstein gans},
  author={Gulrajani, Ishaan and Ahmed, Faruk and Arjovsky, Martin and Dumoulin, Vincent and Courville, Aaron C},
  booktitle={Advances in Neural Information Processing Systems},
  pages={5767--5777},
  year={2017}
}

@article{bengio2013estimating,
  title={Estimating or propagating gradients through stochastic neurons for conditional computation},
  author={Bengio, Yoshua and L{\'e}onard, Nicholas and Courville, Aaron},
  journal={arXiv preprint arXiv:1308.3432},
  year={2013}
}

@article{salakhutdinov2009semantic,
  title = {{Semantic hashing}},
  author = {Salakhutdinov, Ruslan and Hinton, Geoffrey},
  journal = {International Journal of Approximate Reasoning},
  volume = {50},
  number = {7},
  pages = {969--978},
  year = {2009}
 }

@article{maaten2008visualizing,
  title={Visualizing data using t-SNE},
  author={Maaten, Laurens van der and Hinton, Geoffrey},
  journal={Journal of machine learning research},
  volume={9},
  number={Nov},
  pages={2579--2605},
  year={2008}
}


@inproceedings{mikolov2010recurrent,
  title={Recurrent neural network based language model},
  author={Mikolov, Tom{\'a}{\v{s}} and Karafi{\'a}t, Martin and Burget, Luk{\'a}{\v{s}} and {\v{C}}ernock{\`y}, Jan and Khudanpur, Sanjeev},
  booktitle={Eleventh Annual Conference of the International Speech Communication Association},
  year={2010}
}




@inproceedings{kiros2015skip,
  title = {{Skip-thought vectors}},
  author = {Kiros, Ryan and Zhu, Yukun and Salakhutdinov, Ruslan R and Zemel, Richard and Urtasun, Raquel and Torralba, Antonio and Fidler, Sanja},
  booktitle = {Advances in neural information processing systems},
  pages = {3294--3302},
  year = {2015},
}


@article{arjovsky2017wasserstein,
  title={Wasserstein gan},
  author={Arjovsky, Martin and Chintala, Soumith and Bottou, L{\'e}on},
  journal={arXiv preprint arXiv:1701.07875},
  year={2017}
}


@book{burkard2009assignment,
  title={Assignment problems},
  author={Burkard, Rainer E and Dell'Amico, Mauro and Martello, Silvano},
  year={2009},
  publisher={Springer}
}

@article{berthelot2018understanding,
  title={Understanding and improving interpolation in autoencoders via an adversarial regularizer},
  author={Berthelot, David and Raffel, Colin and Roy, Aurko and Goodfellow, Ian},
  journal={arXiv preprint arXiv:1807.07543},
  year={2018}
}

@inproceedings{huang2017unsupervised,
  title={Unsupervised Triplet Hashing for Fast Image Retrieval},
  author={Huang, Shanshan and Xiong, Yichao and Zhang, Ya and Wang, Jia},
  booktitle={Proceedings of the on Thematic Workshops of ACM Multimedia},
  pages={84--92},
  year={2017},
  address={Mountain View, CA}
}

@inproceedings{do2016learning,
  title={Learning to hash with binary deep neural network},
  author={Do, Thanh-Toan and Doan, Anh-Dzung and Cheung, Ngai-Man},
  booktitle={European Conference on Computer Vision},
  pages={219--234},
  year={2016},
  organization={Springer}
}
@inproceedings{he2013k,
  title={K-means hashing: An affinity-preserving quantization method for learning binary compact codes},
  author={He, Kaiming and Wen, Fang and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={2938--2945},
  year={2013}
}


@inproceedings{qiu2017deep,
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@article{huang2018flexps,
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@inproceedings{Poseidon,
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@inproceedings{cheng2016wide,
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@techreport{Report:Li_Zhang_L0,
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@techreport{Report:Li_CC_v0,
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@techreport{Report:RPCodeNonlinear2014,
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@techreport{Report:CCCS,
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@techreport{Report:VSCCCS,
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@inproceedings{li2012unsupervised,
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@inproceedings{Proc:Du15-FSASL,
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@inproceedings{Proc:Nie16-SOGFS,
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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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@misc{annoy,
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@inproceedings{Proc:Huang_CIKM13,
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@inproceedings{Proc:Mueller_AAAI16,
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  booktitle = {Proceedings of the 27th {ACM} International Conference on Information
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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:Karras_ICLR18,
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@inproceedings{Proc:Zhu_ICCV17,
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               Tengyu Ma and
               Andrej Risteski},
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  year      = {2019}
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@techreport{arXiv:Ramesh_2018,
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@techreport{arXiv:Yang_2018,
  author    = {Tao Yang and
               Georgios Arvanitidis and
               Dongmei Fu and
               Xiaogang Li and
               S{\o}ren Hauberg},
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  year      = {2018}
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@techreport{arXiv:Arjovsky_2017,
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@inproceedings{li2017deep,
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@inproceedings{gui2018r2sdh,
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@inproceedings{yuan2020central,
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               Tao Wang and
               Xiaopeng Zhang and
               Francis E. H. Tay and
               Zequn Jie and
               Wei Liu and
               Jiashi Feng},
  title     = {Central Similarity Quantization for Efficient Image and Video Retrieval},
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@inproceedings{jin2020ssah,
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               Shangchen Zhou and
               Yao Liu and
               Chao Chen and
               Xiaoshuai Sun and
               Hongxun Yao and
               Xian{-}Sheng Hua},
  title     = {{SSAH:} Semi-Supervised Adversarial Deep Hashing with Self-Paced Hard
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  address   = {New York, NY},
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  year      = {2020}
}


@article{deng2019two,
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               Tongliang Liu and
               Dacheng Tao},
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               David Warde{-}Farley and
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  title     = {Generative adversarial networks},
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@inproceedings{cao2018deep,
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               Mingsheng Long and
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@inproceedings{sablayrolles2017should,
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  year={2017},
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               Lianli Gao and
               Xing Xu and
               Alan Hanjalic and
               Heng Tao Shen},
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  year      = {2018}
}


@article{yu2018multi-trend,
  author    = {Laihang Yu and
               Lin Feng and
               Huibing Wang and
               Li Li and
               Yang Liu and
               Shenglan Liu},
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@article{yan2021deep,
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               Yuxuan Wei and
               Yue Gao},
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               Giorgio Grisetti},
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@article{yang2020adversarial,
  author    = {Erkun Yang and
               Tongliang Liu and
               Cheng Deng and
               Dacheng Tao},
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  number    = {4},
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  year      = {2020}
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@inproceedings{hansen2020unsupervised,
  author    = {Casper Hansen and
               Christian Hansen and
               Jakob Grue Simonsen and
               Stephen Alstrup and
               Christina Lioma},
  title     = {Unsupervised Semantic Hashing with Pairwise Reconstruction},
  booktitle = {Proceedings of the 43rd International {ACM} {SIGIR} conference on
               research and development in Information Retrieval (SIGIR)},
  address    = {Virtual
               Event, China},
  pages     = {2009--2012},
  year      = {2020}
}


@inproceedings{liu2020joint,
  author    = {Song Liu and
               Shengsheng Qian and
               Yang Guan and
               Jiawei Zhan and
               Long Ying},
  title     = {Joint-modal Distribution-based Similarity Hashing for Large-scale
               Unsupervised Deep Cross-modal Retrieval},
  booktitle = {Proceedings of the 43rd International {ACM} {SIGIR} conference on
               research and development in Information Retrieval (SIGIR)},
  address   = {Virtual
               Event, China},
  pages     = {1379--1388},
  year      = {2020}
}


@inproceedings{qiu2021unsupervised,
  author    = {Zexuan Qiu and
               Qinliang Su and
               Zijing Ou and
               Jianxing Yu and
               Changyou Chen},
  title     = {Unsupervised Hashing with Contrastive Information Bottleneck},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on Artificial
               Intelligence (IJCAI)},  
  address   = {Virtual Event / Montreal, Canada},
  pages     = {959--965},
  year      = {2021}
}


@inproceedings{ong2016improved,
  author    = {Eng{-}Jon Ong and
               Miroslaw Bober},
  title     = {Improved Hamming Distance Search Using Variable Length Hashing},
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  address   = {Las Vegas, NV},
  pages     = {2000--2008},
  year      = {2016}
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@inproceedings{jiang2015revisiting,
  author    = {Ke Jiang and
               Qichao Que and
               Brian Kulis},
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  address   = {Boston, MA},
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  year      = {2015}
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@inproceedings{do2017simultaneous,
  author    = {Thanh{-}Toan Do and
               Dang{-}Khoa Le Tan and
               Trung T. Pham and
               Ngai{-}Man Cheung},
  title     = {Simultaneous Feature Aggregating and Hashing for Large-Scale Image
               Search},
  booktitle = {Proceedings of the 2017 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Honolulu, HI},
  pages     = {4217--4226},
  year      = {2017}
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@inproceedings{chen2018deep,
  author    = {Zhixiang Chen and
               Xin Yuan and
               Jiwen Lu and
               Qi Tian and
               Jie Zhou},
  title     = {Deep Hashing via Discrepancy Minimization},
  booktitle = {Proceedings of the 2018 {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Salt Lake City, UT},
  pages     = {6838--6847},
  year      = {2018}
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@inproceedings{li2019neighborhood,
  author    = {Shuyan Li and
               Zhixiang Chen and
               Jiwen Lu and
               Xiu Li and
               Jie Zhou},
  title     = {Neighborhood Preserving Hashing for Scalable Video Retrieval},
  booktitle = {Proceedings of the 2019 {IEEE/CVF} International Conference on Computer Vision (ICCV)},
  address   = {Seoul, Korea},
  pages     = {8211--8220},
  year      = {2019}
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@inproceedings{li2017losha,
  author    = {Jinfeng Li and
               James Cheng and
               Fan Yang and
               Yuzhen Huang and
               Yunjian Zhao and
               Xiao Yan and
               Ruihao Zhao},
  title     = {{LoSHa}: {A} General Framework for Scalable Locality Sensitive Hashing},
  booktitle = {Proceedings of the 40th International {ACM} {SIGIR} Conference on
               Research and Development in Information Retrieval (SIGIR)},
  address   = {Shinjuku, Tokyo,
               Japan},
  pages     = {635--644},
  year      = {2017}
}

@article{qi2017distributed,
  author    = {Lianyong Qi and
               Xuyun Zhang and
               Wanchun Dou and
               Qiang Ni},
  title     = {A Distributed Locality-Sensitive Hashing-Based Approach for Cloud
               Service Recommendation From Multi-Source Data},
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  year      = {2017}
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@inproceedings{chen2019locality,
  author    = {Lin Chen and
               Hossein Esfandiari and
               Gang Fu and
               Vahab S. Mirrokni},
  title     = {Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss
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  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {Vancouver, Canada},
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  year      = {2019}
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  author    = {Amir Zandieh and
               Navid Nouri and
               Ameya Velingker and
               Michael Kapralov and
               Ilya P. Razenshteyn},
  title     = {Scaling up Kernel Ridge Regression via Locality Sensitive Hashing},
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  year      = {2020}
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@inproceedings{le2020stochastically,
  author    = {Dung D. Le and
               Hady W. Lauw},
  title     = {Stochastically Robust Personalized Ranking for {LSH} Recommendation
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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{li2020locality,
  author    = {Yifan Lei and
               Qiang Huang and
               Mohan S. Kankanhalli and
               Anthony K. H. Tung},
  title     = {Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring},
  booktitle = {Proceedings of the 2020 International Conference on Management of
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  address   = {Online conference [Portland, OR, USA]
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  pages     = {2589--2599},
  year      = {2020}
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  author    = {Shabnam Daghaghi and
               Tharun Medini and
               Nicholas Meisburger and
               Beidi Chen and
               Mengnan Zhao and
               Anshumali Shrivastava},
  title     = {A Tale of Two Efficient and Informative Negative Sampling Distributions},
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@inproceedings{chen2021mongoose,
  author    = {Beidi Chen and
               Zichang Liu and
               Binghui Peng and
               Zhaozhuo Xu and
               Jonathan Lingjie Li and
               Tri Dao and
               Zhao Song and
               Anshumali Shrivastava and
               Christopher R{\'{e}}},
  title     = {{MONGOOSE:} {A} Learnable {LSH} Framework for Efficient Neural Network
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  booktitle = {Proceedings of the 9th International Conference on Learning Representations (ICLR)},
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  year      = {2021}
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               Dino Sejdinovic and
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  booktitle = {Advances in Neural Information Processing Systems  (NIPS)},
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	pages={1667--1680},
	year={2012},
	publisher={IEEE}
}
@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},
  author={Andoni, Alexandr and Indyk, Piotr and Laarhoven, Thijs and Razenshteyn, Ilya and Schmidt, Ludwig},
  journal={arXiv preprint arXiv:1509.02897},
  year={2015}
}

@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},
  pages={115},
  year={2017},
  publisher={Nature Publishing Group}
}
@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},
  booktitle={Machine Learning for Healthcare Conference},
  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},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1891--1898},
  year={2014}
}
@article{karu1996fingerprint,
  title={Fingerprint classification},
  author={Karu, Kalle and Jain, Anil K},
  journal={Pattern recognition},
  volume={29},
  number={3},
  pages={389--404},
  year={1996},
  publisher={Elsevier}
}
%%%%%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}
}

@article{tehranipoor2010survey,
  title={A survey of hardware trojan taxonomy and detection},
  author={Tehranipoor, Mohammad and Koushanfar, Farinaz},
  journal={IEEE Design \& Test of Computers},
  volume={27},
  number={1},
  year={2010},
  publisher={IEEE}
}
@inproceedings{wei2012hardware,
  title={Hardware Trojan horse benchmark via optimal creation and placement of malicious circuitry},
  author={Wei, Sheng and Li, Kai and Koushanfar, Farinaz and Potkonjak, Miodrag},
  booktitle={Proceedings of the 49th Annual Design Automation Conference},
  pages={90--95},
  year={2012},
  organization={ACM}
}
@inproceedings{chakraborty2009hardware,
  title={Hardware Trojan: Threats and emerging solutions},
  author={Chakraborty, Rajat Subhra and Narasimhan, Seetharam and Bhunia, Swarup},
  booktitle={{IEEE} International High Level Design Validation and Test Workshop ({HLDVT})},
  pages={166--171},
  year={2009},
  organization={IEEE}
}
@inproceedings{jin2008hardware,
  title={Hardware Trojan detection using path delay fingerprint},
  author={Jin, Yier and Makris, Yiorgos},
  booktitle={2008 IEEE International Workshop on Hardware-Oriented Security and Trust},
  pages={51--57},
  year={2008}
}
@inproceedings{chakraborty2009security,
  title={Security against hardware Trojan through a novel application of design obfuscation},
  author={Chakraborty, Rajat Subhra and Bhunia, Swarup},
  booktitle={2009 {IEEE}/{ACM} International Conference on Computer-Aided Design},
  pages={113--116},
  year={2009}
}
@article{bhunia2013protection,
  title={Protection against hardware trojan attacks: Towards a comprehensive solution},
  author={Bhunia, Swarup and Abramovici, Miron and Agrawal, Dakshi and Bradley, Paul and Hsiao, Michael S and Plusquellic, Jim and Tehranipoor, Mohammad},
  journal={{IEEE} Design \& Test},
  volume={30},
  number={3},
  pages={6--17},
  year={2013}
}

@article{xiao2016hardware,
  author    = {Kan Xiao and
               Domenic Forte and
               Yier Jin and
               Ramesh Karri and
               Swarup Bhunia and
               Mark M. Tehranipoor},
  title     = {Hardware Trojans: Lessons Learned after One Decade of Research},
  journal   = {{ACM} Trans. Design Autom. Electr. Syst.},
  volume    = {22},
  number    = {1},
  pages     = {6:1--6:23},
  year      = {2016}
}

@inproceedings{ghandali2016design,
  title={A design methodology for stealthy parametric Trojans and its application to bug attacks},
  author={Ghandali, Samaneh and Becker, Georg T and Holcomb, Daniel and Paar, Christof},
  booktitle={International Conference on Cryptographic Hardware and Embedded Systems},
  pages={625--647},
  year={2016}
}
@incollection{narasimhan2012hardware,
  title={Hardware trojan detection},
  author={Narasimhan, Seetharam and Bhunia, Swarup},
  booktitle={Introduction to Hardware Security and Trust},
  pages={339--364},
  year={2012}
}
@article{narasimhan2013hardware,
  title={Hardware Trojan detection by multiple-parameter side-channel analysis},
  author={Narasimhan, Seetharam and Du, Dongdong and Chakraborty, Rajat Subhra and Paul, Somnath and Wolff, Francis G and Papachristou, Christos A and Roy, Kaushik and Bhunia, Swarup},
  journal={{IEEE} Transactions on computers},
  volume={62},
  number={11},
  pages={2183--2195},
  year={2013}
}
@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}
}

@incollection{mccloskey1989catastrophic,
	title={Catastrophic interference in connectionist networks: The sequential learning problem},
	author={McCloskey, Michael and Cohen, Neal J},
	booktitle={Psychology of learning and motivation},
	volume={24},
	pages={109--165},
	year={1989},
	publisher={Elsevier}
}

@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},
  author={Parhi, Megha and Lao, Yingjie and Parhi, Keshab K},
  booktitle={Asilomar Conference on Signals, Systems and Computers},
  pages={1261--1265},
  year={2014},
  organization={IEEE}
}

@inproceedings{lao2016data,
  title={Data-canonic real {FFT} flow-graphs for composite lengths},
  author={Lao, Yingjie and Parhi, Keshab K},
  booktitle={IEEE International Workshop on Signal Processing Systems ({SiPS})},
  pages={189--194},
  year={2016},
  organization={IEEE}
}

@inproceedings{lao2015canonic,
  title={Canonic real-valued radix-2n {FFT} computations},
  author={Lao, Yingjie and Parhi, Keshab K},
  booktitle={Asilomar Conference on Signals, Systems and Computers},
  pages={441--446},
  year={2015},
  organization={IEEE}
}

@article{lao2017canonic,
  title={Canonic {FFT} flow graphs for real-valued even/odd symmetric inputs},
  author={Lao, Yingjie and Parhi, Keshab K},
  journal={{EURASIP} Journal on Advances in Signal Processing},
  volume={2017},
  number={1},
  pages={45},
  year={2017},
  publisher={Nature Publishing Group}
}

@inproceedings{qiu2018systematic,
  title={A Systematic Method for Approximate Circuit Design Using Feature Selection},
  author={Qiu, Ling and Lao, Yingjie},
  booktitle={{IEEE} International Symposium on Circuits and Systems ({ISCAS})},
  pages={1--5},
  year={2018},
  organization={IEEE}
}


@inproceedings{szegedy2015going,
  title={Going deeper with convolutions},
  author={Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke, Vincent and Rabinovich, Andrew},
  booktitle={Proceedings of the {IEEE} conference on computer vision and pattern recognition},
  pages={1--9},
  year={2015}
}

@inproceedings{sermanet2013overfeat,
  title={Overfeat: Integrated recognition, localization and detection using convolutional networks},
  author={Sermanet, Pierre and Eigen, David and Zhang, Xiang and Mathieu, Micha{\"e}l and Fergus, Robert and Lecun, Yann},
  booktitle={International Conference on Learning Representations ({ICLR})},
  year={2013}
}

@article{liang2016deep,
  title={Why deep neural networks for function approximation?},
  author={Liang, Shiyu and Srikant, R},
  journal={International Conference on Learning Representations ({ICLR})},
  year={2016}
}

@article{chen2017eyeriss,
  title={Eyeriss: An energy-efficient reconfigurable accelerator for deep convolutional neural networks},
  author={Chen, Yu-Hsin and Krishna, Tushar and Emer, Joel S and Sze, Vivienne},
  journal={{IEEE} Journal of Solid-State Circuits},
  volume={52},
  number={1},
  pages={127--138},
  year={2017},
  publisher={IEEE}
}

@inproceedings{yoo20151,
  title={A 1.93 tops/w scalable deep learning/inference processor with tetra-parallel mimd architecture for big data applications},
  author={Yoo, Hoi-Jun and Park, Seongwook and Bong, Kyeongryeol and Shin, Dongjoo and Lee, Jinmook and Choi, Sungpill},
  booktitle={{IEEE} International Solid-State Circuits Conference},
  pages={80--81},
  year={2015},
  organization={IEEE}
}

@inproceedings{du2015shidiannao,
  title={{ShiDianNao}: Shifting vision processing closer to the sensor},
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               Vasin Wongrassamee and
               Emil C. Lupu and
               Fabio Roli},
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  year={2017},
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  author    = {Bryant Chen and
               Wilka Carvalho and
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               Heiko Ludwig and
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               Ian M. Molloy and
               Biplav Srivastava},
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  year      = {2019}
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@inproceedings{tran2018spectral,
  author    = {Brandon Tran and
               Jerry Li and
               Aleksander Madry},
  title     = {Spectral Signatures in Backdoor Attacks},
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  year      = {2018}
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@inproceedings{gao2019strip,
  author    = {Yansong Gao and
               Change Xu and
               Derui Wang and
               Shiping Chen and
               Damith Chinthana Ranasinghe and
               Surya Nepal},
  title     = {{STRIP:} a defence against trojan attacks on deep neural networks},
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@article{li2020rethinking,
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@inproceedings{wang2019neural,
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  title     = {Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural
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@inproceedings{chen2019deepinspect,
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  year      = {2019}
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@inproceedings{qiao2019defending,
  author    = {Ximing Qiao and
               Yukun Yang and
               Hai Li},
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  year      = {2019}
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@article{turner2019label,
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@inproceedings{tan2019bypassing,
  author    = {Te Juin Lester Tan and
               Reza Shokri},
  title     = {Bypassing Backdoor Detection Algorithms in Deep Learning},
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@inproceedings{clements2019hardware,
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@article{gu2019badnets,
  author    = {Tianyu Gu and
               Kang Liu and
               Brendan Dolan{-}Gavitt and
               Siddharth Garg},
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@inproceedings{xie2019dba,
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@inproceedings{liu2020reflection,
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@inproceedings{nguyen2021wanet,
  author    = {Tuan Anh Nguyen and
               Anh Tuan Tran},
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  year      = {2021}
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@inproceedings{doan2019adversarial,
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@inproceedings{doan2021interpretable,
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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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  title     = {CleaNN: Accelerated Trojan Shield for Embedded Neural Networks},
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  year      = {2019}
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@inproceedings{nguyen2021distributional,
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@article{subedar2019deep,
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  year={2019}
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  booktitle = {Proceedings of the 30th {USENIX} Security Symposium (USENIX Security)},
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  year      = {2021}
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  author    = {Yuchi Tian and
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               Suman Jana and
               Baishakhi Ray},
  title     = {DeepTest: automated testing of deep-neural-network-driven autonomous
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  year      = {2018}
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  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
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  address   = {New Orleans, LA},
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  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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  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}
}



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  author    = {Avishek Joey Bose and
               Gauthier Gidel and
               Hugo Berard and
               Andre Cianflone and
               Pascal Vincent and
               Simon Lacoste{-}Julien and
               William L. Hamilton},
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  year      = {2020}
}

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  year      = {2018}
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@article{xue2022imperceptible,
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}

@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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  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{cheng2021deep,
  author    = {Siyuan Cheng and
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  booktitle = {Proceedings of the thirty-Fifth {AAAI} Conference on Artificial Intelligence (AAAI)},
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@inproceedings{nguyen2020input,
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  year      = {2020}
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@inproceedings{huang2020metapoison,
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               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},
  journal={arXiv preprint arXiv:1907.11692},
  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},
  author={Jin, Feihu and Lu, Jinliang and Zhang, Jiajun and Zong, Chengqing},
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  year={2022}
}


@article{qin2021learning,
  title={Learning how to ask: Querying LMs with mixtures of soft prompts},
  author={Qin, Guanghui and Eisner, Jason},
  journal={arXiv preprint arXiv:2104.06599},
  year={2021}
}

@inproceedings{zhong2021factual,
  author    = {Zexuan Zhong and
               Dan Friedman and
               Danqi Chen},
  title     = {Factual Probing Is {[MASK]:} Learning vs. Learning to Recall},
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  pages     = {5017--5033},
  year      = {2021}
}


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               Sebastian Riedel and
               Patrick S. H. Lewis and
               Anton Bakhtin and
               Yuxiang Wu and
               Alexander H. Miller},
  title     = {Language Models as Knowledge Bases?},
  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)},
  address   = {Hong Kong, China},
  pages     = {2463--2473}
}



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@inproceedings{bossard2014food,
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@article{maji2013fine,
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@inproceedings{xiao2010sun,
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               James Hays and
               Krista A. Ehinger and
               Aude Oliva and
               Antonio Torralba},
  title     = {{SUN} database: Large-scale scene recognition from abbey to zoo},
  booktitle = {Proceedings of the Twenty-Third {IEEE} Conference on Computer Vision and Pattern
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@inproceedings{fei2004learning,
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@article{zhao2022constrained,
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@inproceedings{yu2019linear,
  author    = {Hao Yu and
               Rong Jin and
               Sen Yang},
  title     = {On the Linear Speedup Analysis of Communication Efficient Momentum
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  booktitle = {Proceedings of the 36th International Conference on Machine Learning (ICML)},
  address = {Long Beach, CA},
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  year      = {2019}
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@article{zhou2018convergence,
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@inproceedings{chen2022convergence,
  author    = {Xiangyi Chen and
               Belhal Karimi and
               Weijie Zhao 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},
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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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  journal   = {{IEEE} Commun. Surv. Tutorials},
  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}
}

@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)},
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  year      = {2020}
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@inproceedings{haddadpour2021federated,
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               Aryan Mokhtari and
               Mehrdad Mahdavi},
  title     = {Federated Learning with Compression: Unified Analysis and Sharp Guarantees},
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  year      = {2021}
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@inproceedings{dettmers20168,
  author    = {Tim Dettmers},
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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},
  booktitle = {Proceedings of the 7th International Conference on Learning Representations (ICLR)},
  address   = {New Orleans, LA},
  year      = {2019}
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@inproceedings{basu2019qsparse,
  author    = {Debraj Basu and
               Deepesh Data and
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@inproceedings{yu2021cross,
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@inproceedings{yu2022u,
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@misc{dong2021cswin,
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  title     = {{CrossFormer}: {A} Versatile Vision Transformer Hinging on Cross-scale
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  title     = {Multiscale Vision Transformers},
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@inproceedings{doan2020daba,
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@inproceedings{zhu2019transferable,
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  year      = {2019}
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}

@inproceedings{naseer2021intriguing,
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               Kanchana Ranasinghe and
               Salman Khan and
               Munawar Hayat and
               Fahad Shahbaz Khan and
               Ming{-}Hsuan Yang},
  title     = {Intriguing Properties of Vision Transformers},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  address   = {virtual},
  pages     = {23296--23308},
  year      = {2021}
}


@inproceedings{mahmood2021robustness,
  author    = {Kaleel Mahmood and
               Rigel Mahmood and
               Marten van Dijk},
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  booktitle = {Proceedings of the 2021 {IEEE/CVF} International Conference on Computer Vision (ICCV)},
  address   = {Montreal, Canada},
  pages     = {7818--7827},
  year      = {2021}
}


@article{shao2021adversarial,
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  author={Shao, Rulin and Shi, Zhouxing and Yi, Jinfeng and Chen, Pin-Yu and Hsieh, Cho-Jui},
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  year={2021}
}


@inproceedings{naseer2022improving,
  author    = {Muzammal Naseer and
               Kanchana Ranasinghe and
               Salman Khan and
               Fahad Shahbaz Khan and
               Fatih Porikli},
  title     = {On Improving Adversarial Transferability of Vision Transformers},
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  address  = {Virtual Event},
  year      = {2022}
}


@article{joshi2021adversarial,
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  author={Joshi, Ameya and Jagatap, Gauri and Hegde, Chinmay},
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  year={2021}
}

@inproceedings{doan2020februus,
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               Ehsan Abbasnejad and
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               Event / Austin, TX},
  pages     = {897--912},
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}

@article{udeshi2019model,
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               Shanshan Peng and
               Gerald Woo and
               Lionell Loh and
               Louth Rawshan and
               Sudipta Chattopadhyay},
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  journal   = {{IEEE} Trans. Reliab.},
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  number    = {2},
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  year      = {2022}
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@inproceedings{qiu2021deepsweep,
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               Yi Zeng and
               Shangwei Guo and
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               Bhavani M. Thuraisingham},
  title     = {DeepSweep: An Evaluation Framework for Mitigating {DNN} Backdoor Attacks
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  pages     = {363--377},
  year      = {2021}
}


@inproceedings{kolesnikov2020big,
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  address = {Glasgow, UK},
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  year={2020}
}


@article{lv2021dbia,
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  journal={arXiv preprint arXiv:2111.11870},
  year={2021}
}

@inproceedings{doan2022marksman,
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  year={2022}
}

@article{pananjady2016linear,
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@article{tsakiris2020algebraic,
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@inproceedings{Proc:zhang2021sparse,
  author    = {Hang Zhang and
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  booktitle = {Proceedings of the {IEEE} International Symposium on Information Theory (ISIT)},
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@article{zhang2022benefits,
  author    = {Hang Zhang and
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  journal   = {{IEEE} Trans. Inf. Theory},
  volume    = {68},
  number    = {4},
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@inproceedings{zhang2019permutation,
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@phdthesis{chandar2010sparse,
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@article{zhang2015deterministic,
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@inproceedings{sarvotham2006sudocodes,
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@inproceedings{kudekar2010effect,
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@inproceedings{khajehnejad2011summary,
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	date-modified = {2021-05-04 18:13:49 -0400},
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	year = {2011}}

@article{jafarpour2009efficient,
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@article{zdeborova2016statistical,
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@misc{hzhangdensityevolve,
	author = {Hang Zhang and Afshin Abdi and Faramarz Fekri},
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	title = {A General Framework for the Design of Sparse Measurements using Density Evolution}}

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@article{gallager1962low,
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@book{pearl2014probabilistic,
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@article{donoho2016high,
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@article{schniter2015compressive,
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}


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	title = {A General Framework for the Design of Sparse Measurements using Density Evolution}}

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@inproceedings{aryacoherenceicassp2018,
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%% LaTeX2e file `quickbib.bib'
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%% from source `dense-subhypergraph-note' on 2020/09/08.



%%


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@inproceedings{zhang2020dynamic,
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@inproceedings{singhal2021federated,
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@inproceedings{rothchild2020fetchsgd,
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  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},
  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}",
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    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{karimi2016linear,
  author    = {Hamed Karimi and
               Julie Nutini and
               Mark Schmidt},
  title     = {Linear Convergence of Gradient and Proximal-Gradient Methods Under
               the Polyak-{\L}ojasiewicz Condition},
  booktitle = {Proceedings of European Conference on Machine Learning and Knowledge Discovery in Databases ({ECML}-{PKDD})},
  address = {Riva del Garda, Italy},
  pages     = {795--811},
  year      = {2016}
}

@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{zhang2016parallel,
  title={Parallel SGD: When does averaging help?},
  author={Zhang, Jian and De Sa, Christopher and Mitliagkas, Ioannis and R{\'e}, Christopher},
  journal={arXiv preprint arXiv:1606.07365},
  year={2016}
}

@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{seide20141,
  title={1-bit stochastic gradient descent and its application to data-parallel distributed training of speech dnns},
  author={Seide, Frank and Fu, Hao and Droppo, Jasha and Li, Gang and Yu, Dong},
  booktitle={Fifteenth Annual Conference of the International Speech Communication Association},
  year={2014}
}


@inproceedings{zhang2017zipml,
  title={Zipml: Training linear models with end-to-end low precision, and a little bit of deep learning},
  author={Zhang, Hantian and Li, Jerry and Kara, Kaan and Alistarh, Dan and Liu, Ji and Zhang, Ce},
  booktitle={Proceedings of the 34th International Conference on Machine Learning-Volume 70},
  pages={4035--4043},
  year={2017},
}




@inproceedings{abadi2016tensorflow,
  title={Tensorflow: A system for large-scale machine learning},
  author={Abadi, Mart{\'\i}n and Barham, Paul and Chen, Jianmin and Chen, Zhifeng and Davis, Andy and Dean, Jeffrey and Devin, Matthieu and Ghemawat, Sanjay and Irving, Geoffrey and Isard, Michael and others},
  booktitle={12th $\{$USENIX$\}$ Symposium on Operating Systems Design and Implementation ($\{$OSDI$\}$ 16)},
  pages={265--283},
  year={2016}
}

@article{paszke2017automatic,
  title={Automatic differentiation in pytorch},
  author={Paszke, Adam and Gross, Sam and Chintala, Soumith and Chanan, Gregory and Yang, Edward and DeVito, Zachary and Lin, Zeming and Desmaison, Alban and Antiga, Luca and Lerer, Adam},
  year={2017}
}

@inproceedings{Seide2016CNTKMO,
  title={CNTK: Microsoft's Open-Source Deep-Learning Toolkit},
  author={Frank Seide and Amit Agarwal},
  booktitle={KDD},
  year={2016}
}
@inproceedings{recht2011hogwild,
  title={Hogwild: A lock-free approach to parallelizing stochastic gradient descent},
  author={Recht, Benjamin and Re, Christopher and Wright, Stephen and Niu, Feng},
  booktitle={Advances in neural information processing systems},
  pages={693--701},
  year={2011}
}

@inproceedings{de2015taming,
  title={Taming the wild: A unified analysis of hogwild-style algorithms},
  author={De Sa, Christopher M and Zhang, Ce and Olukotun, Kunle and R{\'e}, Christopher},
  booktitle={Advances in neural information processing systems},
  pages={2674--2682},
  year={2015}
}

@inproceedings{lian2015asynchronous,
  title={Asynchronous parallel stochastic gradient for nonconvex optimization},
  author={Lian, Xiangru and Huang, Yijun and Li, Yuncheng and Liu, Ji},
  booktitle={Advances in Neural Information Processing Systems},
  pages={2737--2745},
  year={2015}
}

@inproceedings{agarwal2011distributed,
  title={Distributed delayed stochastic optimization},
  author={Agarwal, Alekh and Duchi, John C},
  booktitle={Advances in Neural Information Processing Systems},
  pages={873--881},
  year={2011}
}
@inproceedings{zhou2018distributed,
  title={Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?},
  author={Zhou, Zhengyuan and Mertikopoulos, Panayotis and Bambos, Nicholas and Glynn, Peter W and Ye, Yinyu and Li, Li-Jia and Li, Fei-Fei},
  booktitle={ICML 2018-35th International Conference on Machine Learning},
  pages={1--10},
  year={2018}
}

@article{chen2016revisiting,
  title={Revisiting distributed synchronous SGD},
  author={Chen, Jianmin and Pan, Xinghao and Monga, Rajat and Bengio, Samy and Jozefowicz, Rafal},
  journal={arXiv preprint arXiv:1604.00981},
  year={2016}
}

@inproceedings{gupta2015deep,
  title={Deep learning with limited numerical precision},
  author={Gupta, Suyog and Agrawal, Ankur and Gopalakrishnan, Kailash and Narayanan, Pritish},
  booktitle={International Conference on Machine Learning},
  pages={1737--1746},
  year={2015}
}

@inproceedings{na2017chip,
  title={On-chip training of recurrent neural networks with limited numerical precision},
  author={Na, Taesik and Ko, Jong Hwan and Kung, Jaeha and Mukhopadhyay, Saibal},
  booktitle={2017 International Joint Conference on Neural Networks (IJCNN)},
  pages={3716--3723},
  year={2017},
  organization={IEEE}
}

@inproceedings{wangni2018gradient,
  title={Gradient sparsification for communication-efficient distributed optimization},
  author={Wangni, Jianqiao and Wang, Jialei and Liu, Ji and Zhang, Tong},
  booktitle={Advances in Neural Information Processing Systems},
  pages={1299--1309},
  year={2018}
}

@inproceedings{wen2017terngrad,
  title={Terngrad: Ternary gradients to reduce communication in distributed deep learning},
  author={Wen, Wei and Xu, Cong and Yan, Feng and Wu, Chunpeng and Wang, Yandan and Chen, Yiran and Li, Hai},
  booktitle={Advances in neural information processing systems (NIPS)},
  pages={1509--1519},
  address ={Long Beach, CA},
  year={2017}
}

@inproceedings{strom2015scalable,
  title={Scalable distributed DNN training using commodity GPU cloud computing},
  author={Strom, Nikko},
  booktitle={Sixteenth Annual Conference of the International Speech Communication Association},
  year={2015}
}

@inproceedings{dryden2016communication,
  title={Communication quantization for data-parallel training of deep neural networks},
  author={Dryden, Nikoli and Moon, Tim and Jacobs, Sam Ade and Van Essen, Brian},
  booktitle={2016 2nd Workshop on Machine Learning in HPC Environments (MLHPC)},
  pages={1--8},
  year={2016},
  organization={IEEE}
}


@article{aji2017sparse,
  title={Sparse communication for distributed gradient descent},
  author={Aji, Alham Fikri and Heafield, Kenneth},
  journal={arXiv preprint arXiv:1704.05021},
  year={2017}
}

@inproceedings{sun2017meprop,
  title={meprop: Sparsified back propagation for accelerated deep learning with reduced overfitting},
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@article{mahdavi2012trading,
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@inproceedings{multile-kernel-noisy,
  author    = {Tianbao Yang and
               Mehrdad Mahdavi and
               Rong Jin and
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@article{yang2012efficient,
  author    = {Tianbao Yang and
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  journal   = {Machine Learning},
  volume    = {98},
  number    = {3},
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@inproceedings{mahdavi2015lower,
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  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},
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  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}
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  year={2013},
  publisher={National Acad Sciences}
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@article{omran2008global,
  title={Global-best harmony search},
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  year={2008},
  publisher={Elsevier}
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@article{mahdavi2007improved,
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  pages={1567--1579},
  year={2007},
  publisher={Elsevier}
}


@article{omran2008global,
  title={Global-best harmony search},
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  year={2008},
  publisher={Elsevier}
}



@article{mahdavi2009harmony,
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@article{mahdavi2007improved,
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  author={Mahdavi, Mehrdad and Fesanghary, M and Damangir, E},
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@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},
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  journal={Computer Communications},
  volume={31},
  number={10},
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  year={2008},
  publisher={Elsevier}
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@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}
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@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}
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@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},
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@inproceedings{forsati2008web,
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@inproceedings{forsati2008hybridization,
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@article{mahdavi2012improved,
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@inproceedings{yi2012robust,
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@inproceedings{yang2012nystrom,
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@inproceedings{mahdavi2012online,
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@article{mahdavi2012trading,
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