%%%%%%%%%%%%%%%%%%%%%%%%%%% DP %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{jayaraman2019evaluating,
  title={Evaluating differentially private machine learning in practice},
  author={Jayaraman, Bargav and Evans, David},
  booktitle={28th USENIX Security Symposium (USENIX Security 19)},
  pages={1895--1912},
  year={2019}
}

%%%%%%%%%%%%%%%%%%%%%%%%%%% MIA %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{shokri2017membership,
  title={Membership inference attacks against machine learning models},
  author={Shokri, Reza and Stronati, Marco and Song, Congzheng and Shmatikov, Vitaly},
  booktitle={2017 IEEE symposium on security and privacy (SP)},
  pages={3--18},
  year={2017},
  organization={IEEE}
}

@inproceedings{choquette2021labelonlymia,
  title={Label-only membership inference attacks},
  author={Choquette-Choo, Christopher A and Tramer, Florian and Carlini, Nicholas and Papernot, Nicolas},
  booktitle={International conference on machine learning},
  pages={1964--1974},
  year={2021},
}

@inproceedings{rezaei2021difficulty,
  title={On the difficulty of membership inference attacks},
  author={Rezaei, Shahbaz and Liu, Xin},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={7892--7900},
  year={2021}
}

@inproceedings{del2022leveraging,
  title={Leveraging adversarial examples to quantify membership information leakage},
  author={Del Grosso, Ganesh and Jalalzai, Hamid and Pichler, Georg and Palamidessi, Catuscia and Piantanida, Pablo},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={10399--10409},
  year={2022}
}

@inproceedings{song2021systematic,
  title={Systematic evaluation of privacy risks of machine learning models},
  author={Song, Liwei and Mittal, Prateek},
  booktitle={30th USENIX Security Symposium (USENIX Security 21)},
  pages={2615--2632},
  year={2021}
}

@misc{li2022lleaks,
      title={l-Leaks: Membership Inference Attacks with Logits}, 
      author={Shuhao Li and Yajie Wang and Yuanzhang Li and Yu-an Tan},
      year={2022},
      eprint={2205.06469},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}


%%%%%%%%%%%%%%%%%%%%%%%%%% MIA Defence %%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{guo2017labelsmoothing,
  title = 	 {On Calibration of Modern Neural Networks},
  author =       {Chuan Guo and Geoff Pleiss and Yu Sun and Kilian Q. Weinberger},
  booktitle = 	 {Proceedings of the 34th International Conference on Machine Learning},
  pages = 	 {1321--1330},
  year = 	 {2017},
  editor = 	 {Precup, Doina and Teh, Yee Whye},
  volume = 	 {70},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {06--11 Aug},
  publisher =    {PMLR},
}

@inproceedings{Rafael2019labelsmoothing,
 author = {M\"{u}ller, Rafael and Kornblith, Simon and Hinton, Geoffrey E},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {When does label smoothing help?},
 volume = {32},
 year = {2019}
}

@misc{pereyra2017confidencepenalty,
      title={Regularizing Neural Networks by Penalizing Confident Output Distributions}, 
      author={Gabriel Pereyra and George Tucker and Jan Chorowski and Łukasz Kaiser and Geoffrey Hinton},
      year={2017},
      eprint={1701.06548},
      archivePrefix={arXiv},
      primaryClass={cs.NE}
}

@inproceedings{nasr2018advreg,
  title={Machine learning with membership privacy using adversarial regularization},
  author={Nasr, Milad and Shokri, Reza and Houmansadr, Amir},
  booktitle={Proceedings of the 2018 ACM SIGSAC conference on computer and communications security},
  pages={634--646},
  year={2018}
}

@inproceedings{jia2019memguard,
  title={Memguard: Defending against black-box membership inference attacks via adversarial examples},
  author={Jia, Jinyuan and Salem, Ahmed and Backes, Michael and Zhang, Yang and Gong, Neil Zhenqiang},
  booktitle={Proceedings of the 2019 ACM SIGSAC conference on computer and communications security},
  pages={259--274},
  year={2019}
}

@inproceedings{shejwalkar2021dmp,
  title={Membership privacy for machine learning models through knowledge transfer},
  author={Shejwalkar, Virat and Houmansadr, Amir},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={35},
  number={11},
  pages={9549--9557},
  year={2021}
}

@inproceedings{wang2021pruning,
  title     = {Against Membership Inference Attack: Pruning is All You Need},
  author    = {Wang, Yijue and Wang, Chenghong and Wang, Zigeng and Zhou, Shanglin and Liu, Hang and Bi, Jinbo and Ding, Caiwen and Rajasekaran, Sanguthevar},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  pages     = {3141--3147},
  year      = {2021}
}


@InProceedings{kaya2021augmia,
  title = 	 {When Does Data Augmentation Help With Membership Inference Attacks?},
  author =       {Kaya, Yigitcan and Dumitras, Tudor},
  booktitle = 	 {Proceedings of the 38th International Conference on Machine Learning},
  pages = 	 {5345--5355},
  year = 	 {2021},
}


@inproceedings{yuan2022samia,
  title={Membership inference attacks and defenses in neural network pruning},
  author={Yuan, Xiaoyong and Zhang, Lan},
  booktitle={31st USENIX Security Symposium (USENIX Security 22)},
  pages={4561--4578},
  year={2022}
}

@inproceedings{tang2022selena,
  title={Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture},
  author={Tang, Xinyu and Mahloujifar, Saeed and Song, Liwei and Shejwalkar, Virat and Nasr, Milad and Houmansadr, Amir and Mittal, Prateek},
  booktitle = {31st {USENIX} Security Symposium ({USENIX} Security)},
  year={2022}
}

@inproceedings{chen2022relaxloss,
  title={RelaxLoss: Defending Membership Inference Attacks without Losing Utility},
  author={Dingfan Chen and Ning Yu and Mario Fritz},
  booktitle={International Conference on Learning Representations},
  year={2022}
}

@inproceedings{yang2023purifier,
  title={Purifier: Defending Data Inference Attacks via Transforming Confidence Scores},
  author={Yang, Ziqi and Wang, Lijin and Yang, Da and Wan, Jie and Zhao, Ziming and Chang, Ee-Chien and Zhang, Fan and Ren, Kui},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={37},
  number={9},
  pages={10871--10879},
  year={2023}
}

@inproceedings{tan2023blessing,
  title = 	 {A Blessing of Dimensionality in Membership Inference through Regularization},
  author =       {Tan, Jasper and LeJeune, Daniel and Mason, Blake and Javadi, Hamid and Baraniuk, Richard G.},
  booktitle = 	 {Proceedings of The 26th International Conference on Artificial Intelligence and Statistics},
  pages = 	 {10968--10993},
  year = 	 {2023},
  editor = 	 {Ruiz, Francisco and Dy, Jennifer and van de Meent, Jan-Willem},
  volume = 	 {206},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {25--27 Apr},
  publisher =    {PMLR},
}

%%%%%%%%%%%%%%%%%%%%%%%%% privacy others %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{fredrikson2015model,
  title={Model inversion attacks that exploit confidence information and basic countermeasures},
  author={Fredrikson, Matt and Jha, Somesh and Ristenpart, Thomas},
  booktitle={Proceedings of the 22nd ACM SIGSAC conference on computer and communications security},
  pages={1322--1333},
  year={2015}
}

@inproceedings{song2017machine,
  title={Machine learning models that remember too much},
  author={Song, Congzheng and Ristenpart, Thomas and Shmatikov, Vitaly},
  booktitle={Proceedings of the 2017 ACM SIGSAC Conference on computer and communications security},
  pages={587--601},
  year={2017}
}

@inproceedings{carlini2019secret,
  title={The secret sharer: Evaluating and testing unintended memorization in neural networks},
  author={Carlini, Nicholas and Liu, Chang and Erlingsson, {\'U}lfar and Kos, Jernej and Song, Dawn},
  booktitle={28th USENIX Security Symposium (USENIX Security 19)},
  pages={267--284},
  year={2019}
}

@inproceedings{salem2020updates,
  title={$\{$Updates-Leak$\}$: Data set inference and reconstruction attacks in online learning},
  author={Salem, Ahmed and Bhattacharya, Apratim and Backes, Michael and Fritz, Mario and Zhang, Yang},
  booktitle={29th USENIX security symposium (USENIX Security 20)},
  pages={1291--1308},
  year={2020}
}

@inproceedings{niv2022reconstructdata,
 author = {Haim, Niv and Vardi, Gal and Yehudai, Gilad and Shamir, Ohad and Irani, Michal},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
 pages = {22911--22924},
 publisher = {Curran Associates, Inc.},
 title = {Reconstructing Training Data From Trained Neural Networks},
 volume = {35},
 year = {2022}
}

%%%%%%%%%%%%%%%%%%%%%%%%% Model Clone %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{nayak2021effectiveness,
  title={Effectiveness of arbitrary transfer sets for data-free knowledge distillation},
  author={Nayak, Gaurav Kumar and Mopuri, Konda Reddy and Chakraborty, Anirban},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={1430--1438},
  year={2021}
}

@misc{jagielski2023students,
      title={Students Parrot Their Teachers: Membership Inference on Model Distillation}, 
      author={Matthew Jagielski and Milad Nasr and Christopher Choquette-Choo and Katherine Lee and Nicholas Carlini},
      year={2023},
      eprint={2303.03446},
      archivePrefix={arXiv},
      primaryClass={cs.CR}
}

%%%%%%%%%%%%%%%%%%%%%%%%% Shortcut %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@article{geirhos2020shortcut,
  title={Shortcut learning in deep neural networks},
  author={Geirhos, Robert and Jacobsen, J{\"o}rn-Henrik and Michaelis, Claudio and Zemel, Richard and Brendel, Wieland and Bethge, Matthias and Wichmann, Felix A},
  journal={Nature Machine Intelligence},
  volume={2},
  number={11},
  pages={665--673},
  year={2020},
  publisher={Nature Publishing Group UK London}
}

%%%%%%%%%%%%%%%%%%%%% Metric Learning %%%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{wen2016centerloss,
   author="Wen, Yandong and Zhang, Kaipeng and Li, Zhifeng and Qiao, Yu",
   editor="Leibe, Bastian and Matas, Jiri and Sebe, Nicu and Welling, Max",
   title="A Discriminative Feature Learning Approach for Deep Face Recognition",
   booktitle="Computer Vision -- ECCV 2016",
   year="2016",
}

@inproceedings{he2018triplet,
  title={Triplet-center loss for multi-view 3d object retrieval},
  author={He, Xinwei and Zhou, Yang and Zhou, Zhichao and Bai, Song and Bai, Xiang},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={1945--1954},
  year={2018}
}

@inproceedings{li2019atcl,
  title={Angular triplet-center loss for multi-view 3d shape retrieval},
  author={Li, Zhaoqun and Xu, Cheng and Leng, Biao},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={33},
  number={01},
  pages={8682--8689},
  year={2019}
}

@inproceedings{wang2019multi,
  title={Multi-similarity loss with general pair weighting for deep metric learning},
  author={Wang, Xun and Han, Xintong and Huang, Weilin and Dong, Dengke and Scott, Matthew R},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={5022--5030},
  year={2019}
}

@article{zhao2020tclfusion,
  title={Deep fusion feature representation learning with hard mining center-triplet loss for person re-identification},
  author={Zhao, Cairong and Lv, Xinbi and Zhang, Zhang and Zuo, Wangmeng and Wu, Jun and Miao, Duoqian},
  journal={IEEE Transactions on Multimedia},
  volume={22},
  number={12},
  pages={3180--3195},
  year={2020},
  publisher={IEEE}
}

@InProceedings{chen2020simclr,
  title = {A Simple Framework for Contrastive Learning of Visual Representations},
  author = {Chen, Ting and Kornblith, Simon and Norouzi, Mohammad and Hinton, Geoffrey},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning},
  pages = 	 {1597--1607},
  year = 	 {2020},
  volume = 	 {119},
}

@inproceedings{rajoli2023tclsampling,
  author={Rajoli, Hossein and Lotfi, Fatemeh and Atyabi, Adham and Afghah, Fatemeh},
  booktitle={2023 57th Annual Conference on Information Sciences and Systems (CISS)}, 
  title={Triplet Loss-less Center Loss Sampling Strategies in Facial Expression Recognition Scenarios}, 
  year={2023},
  volume={},
  number={},
  pages={1-6},
  doi={10.1109/CISS56502.2023.10089734}
}
  

@inproceedings{chen2021simsiam,
  title={Exploring simple siamese representation learning},
  author={Chen, Xinlei and He, Kaiming},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={15750--15758},
  year={2021}
}

@inproceedings{zbontar2021barlow,
  title={Barlow twins: Self-supervised learning via redundancy reduction},
  author={Zbontar, Jure and Jing, Li and Misra, Ishan and LeCun, Yann and Deny, St{\'e}phane},
  booktitle={International Conference on Machine Learning},
  pages={12310--12320},
  year={2021},
  organization={PMLR}
}

@inproceedings{bardes2022vicreg,
  title={{VICR}eg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning},
  author={Adrien Bardes and Jean Ponce and Yann LeCun},
  booktitle={International Conference on Learning Representations},
  year={2022},
  url={https://openreview.net/forum?id=xm6YD62D1Ub}
}

@inproceedings{bardes2022vicregl,
  title={{VICR}egL: Self-Supervised Learning of Local Visual Features},
  author={Adrien Bardes and Jean Ponce and Yann LeCun},
  booktitle={Advances in Neural Information Processing Systems},
  editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
  year={2022},
  url={https://openreview.net/forum?id=ePZsWeGJXyp}
}

@inproceedings{garrido2023sie,  
  title={Self-Supervised Learning of Split Invariant Equivariant Representations},
  author={Garrido, Quentin and Najman, Laurent and LeCun, Yann},
  booktitle={International Conference on Machine Learning},
  year={2023},
  organization={PMLR}
}

@inproceedings{fini2023semiself,
    author = {Fini, Enrico and Astolfi, Pietro and Alahari, Karteek and Alameda-Pineda, Xavier and Mairal, Julien and Nabi, Moin and Ricci, Elisa},
    title  = {Semi-Supervised Learning Made Simple With Self-Supervised Clustering},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month  = {June},
    year   = {2023},
    pages  = {3187-3197}
}

%%%%%%%%%%%%%%%%%%%%%%%%% Pruning %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{frankle2018lotteryticket,
title={The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks},
author={Jonathan Frankle and Michael Carbin},
booktitle={International Conference on Learning Representations},
year={2019},
url={https://openreview.net/forum?id=rJl-b3RcF7},
}

%%%%%%%%%%%%%%%%%%%%%%%%% NN %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@misc{hinton2022forward,
  title={The forward-forward algorithm: Some preliminary investigations},
  author={Hinton, Geoffrey},
  journal={arXiv preprint arXiv:2212.13345},
  year={2022}
}

@misc{openai2023gpt4,
      title={GPT-4 Technical Report}, 
      author={OpenAI},
      year={2023},
      eprint={2303.08774},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}


%%%%%%%%%%%%%%%%%%%%% Robust Learning %%%%%%%%%%%%%%%%%%%%%%
@inproceedings{goodfellow2015fgsm,
  author       = {Ian J. Goodfellow and Jonathon Shlens and Christian Szegedy},
  editor       = {Yoshua Bengio and Yann LeCun},
  title        = {Explaining and Harnessing Adversarial Examples},
  booktitle    = {3rd International Conference on Learning Representations, {ICLR} 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings},
  year         = {2015},
  url          = {http://arxiv.org/abs/1412.6572},
}

@inproceedings{wang2022softrmax,
  title={Enhancing Classifier Conservativeness and Robustness by Polynomiality},
  author={Wang, Ziqi and Loog, Marco},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={13327--13336},
  year={2022}
}

@article{shafahi2019advfree,
  title={Adversarial training for free!},
  author={Shafahi, Ali and Najibi, Mahyar and Ghiasi, Mohammad Amin and Xu, Zheng and Dickerson, John and Studer, Christoph and Davis, Larry S and Taylor, Gavin and Goldstein, Tom},
  journal={Advances in Neural Information Processing Systems},
  volume={32},
  year={2019}
}

%%%%%%%%%%%%%%%%%%%%%%%%%%% Neural Networks %%%%%%%%%%%%%%%%%%%%%%%%%%
@inproceedings{simonyan2015vgg,
  author       = {Karen Simonyan and Andrew Zisserman},
  title        = {Very Deep Convolutional Networks for Large-Scale Image Recognition},
  booktitle    = {3rd International Conference on Learning Representations, {ICLR} 2015,
                  San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings},
  year         = {2015}
}

@inproceedings{he2016resnet,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}

@inproceedings{szegedy2015googlenet,
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},
title = {Going Deeper With Convolutions},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}

@inproceedings{huang2017densenet,
  title={Densely connected convolutional networks},
  author={Huang, Gao and Liu, Zhuang and Van Der Maaten, Laurens and Weinberger, Kilian Q},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={4700--4708},
  year={2017}
}

@inproceedings{howard2019mobilenetv3,
  author={Howard, Andrew and Sandler, Mark and Chen, Bo and Wang, Weijun and Chen, Liang-Chieh and Tan, Mingxing and Chu, Grace and Vasudevan, Vijay and Zhu, Yukun and Pang, Ruoming and Adam, Hartwig and Le, Quoc},
  booktitle={2019 IEEE/CVF International Conference on Computer Vision (ICCV)}, 
  title={Searching for MobileNetV3}, 
  year={2019},
  volume={},
  number={},
  pages={1314-1324},
  doi={10.1109/ICCV.2019.00140}}

@article{lecun1998lenet,
  title={Gradient-based learning applied to document recognition},
  author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick},
  journal={Proceedings of the IEEE},
  volume={86},
  number={11},
  pages={2278--2324},
  year={1998},
  publisher={Ieee}
}

@inproceedings{yang2016han,
    title = "Hierarchical Attention Networks for Document Classification",
    author = "Yang, Zichao  and
      Yang, Diyi  and
      Dyer, Chris  and
      He, Xiaodong  and
      Smola, Alex  and
      Hovy, Eduard",
    editor = "Knight, Kevin  and
      Nenkova, Ani  and
      Rambow, Owen",
    booktitle = "Proceedings of the 2016 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jun,
    year = "2016",
    address = "San Diego, California",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N16-1174",
    doi = "10.18653/v1/N16-1174",
    pages = "1480--1489",
}

%%%%%%%%%%%%%%%%%%%%%%%%%%% Datasets %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@article{krizhevsky2009cifar100,
  title={Learning multiple layers of features from tiny images},
  author={Krizhevsky, Alex and Hinton, Geoffrey and others},
  year={2009},
  publisher={Citeseer}
}

@article{le2015tiny,
  title={Tiny imagenet visual recognition challenge},
  author={Le, Ya and Yang, Xuan},
  journal={CS 231N},
  volume={7},
  number={7},
  pages={3},
  year={2015}
}

@inproceedings{farhangi2022protoformer,
  title={Protoformer: Embedding Prototypes for Transformers},
  author={Farhangi, Ashkan and Sui, Ning and Hua, Nan and Bai, Haiyan and Huang, Arthur and Guo, Zhishan},
  booktitle={Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16--19, 2022, Proceedings, Part I},
  pages={447--458},
  year={2022}
}

@inproceedings{zhifei2017cvpr,
  title={Age Progression/Regression by Conditional Adversarial Autoencoder},
  author={Zhang, Zhifei, Song, Yang, and Qi, Hairong},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  organization={IEEE}
}

@inproceedings{yuval2017svhn,
title	= {Reading Digits in Natural Images with Unsupervised Feature Learning},
author	= {Yuval Netzer and Tao Wang and Adam Coates and Alessandro Bissacco and Bo Wu and Andrew Y. Ng},
year	= {2011},
booktitle	= {NIPS Workshop on Deep Learning and Unsupervised Feature Learning 2011}
}

@article{bell15minc,
	author = "Sean Bell and Paul Upchurch and Noah Snavely and Kavita Bala",
	title = "Material Recognition in the Wild with the Materials in Context Database",
	journal = "Computer Vision and Pattern Recognition (CVPR)",
	year = "2015",
}




%%%%%%%%%%%%%%%%%%%%%%%%%%% OTHERS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@misc{agarap2018relu,
  title={Deep learning using rectified linear units (relu)},
  author={Agarap, Abien Fred},
  journal={arXiv preprint arXiv:1803.08375},
  year={2018}
}

@article{srivastava2014dropout,
  title={Dropout: a simple way to prevent neural networks from overfitting},
  author={Srivastava, Nitish and Hinton, Geoffrey and Krizhevsky, Alex and Sutskever, Ilya and Salakhutdinov, Ruslan},
  journal={The journal of machine learning research},
  volume={15},
  number={1},
  pages={1929--1958},
  year={2014},
  publisher={JMLR. org}
}

@misc{kingma2014adam,
  title={Adam: A method for stochastic optimization},
  author={Kingma, Diederik P and Ba, Jimmy},
  journal={arXiv preprint arXiv:1412.6980},
  year={2014}
}

@inproceedings{wei2022logitnorm,
  title={Mitigating neural network overconfidence with logit normalization},
  author={Wei, Hongxin and Xie, Renchunzi and Cheng, Hao and Feng, Lei and An, Bo and Li, Yixuan},
  booktitle={International Conference on Machine Learning},
  pages={23631--23644},
  year={2022},
  organization={PMLR}
}

@inproceedings{croce2020autoattack,
    title = {Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks},
    author = {Francesco Croce and Matthias Hein},
    booktitle = {ICML},
    year = {2020}
}




@InProceedings{liu2016largemargin,
  title = 	 {Large-Margin Softmax Loss for Convolutional Neural Networks},
  author = 	 {Liu, Weiyang and Wen, Yandong and Yu, Zhiding and Yang, Meng},
  booktitle = 	 {Proceedings of The 33rd International Conference on Machine Learning},
  pages = 	 {507--516},
  year = 	 {2016},
  editor = 	 {Balcan, Maria Florina and Weinberger, Kilian Q.},
  volume = 	 {48},
  series = 	 {Proceedings of Machine Learning Research},
  address = 	 {New York, New York, USA},
  month = 	 {20--22 Jun},
  publisher =    {PMLR},
}




%%%%%%%%%%%%%%%%%%%%%%%%%%% EXAMPLES %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@book{em:86,
  editor  = "Engelmore, Robert and Morgan, Anthony",
  title   = "Blackboard Systems",
  year    = 1986,
  address = "Reading, Mass.",
  publisher = "Addison-Wesley",
}

@inproceedings{c:83,
  author  = "Clancey, William J.",
  year    = 1983,
  title   = "{Communication, Simulation, and Intelligent
Agents: Implications of Personal Intelligent Machines
for Medical Education}",
  booktitle="Proceedings of the Eighth International Joint Conference on Artificial Intelligence {(IJCAI-83)}", 
  pages   = "556-560",
  address = "Menlo Park, Calif",
  publisher = "{IJCAI Organization}",
}
@inproceedings{c:84,
  author  = "Clancey, William J.",
  year    = 1984,
  title   = "{Classification Problem Solving}",
  booktitle = "Proceedings of the Fourth National 
              Conference on Artificial Intelligence",
  pages   = "45-54",
  address = "Menlo Park, Calif.",
  publisher="AAAI Press",
}
@article{r:80,
  author = {Robinson, Arthur L.},
  title = {New Ways to Make Microcircuits Smaller},
  volume = {208},
  number = {4447},
  pages = {1019--1022},
  year = {1980},
  doi = {10.1126/science.208.4447.1019},
  publisher = {American Association for the Advancement of Science},
  issn = {0036-8075},
  URL = {https://science.sciencemag.org/content/208/4447/1019},
  eprint = {https://science.sciencemag.org/content/208/4447/1019.full.pdf},
  journal = {Science},
}
@article{r:80x,
  author  = "Robinson, Arthur L.",
  year    = 1980,
  title   = "{New Ways to Make Microcircuits Smaller---Duplicate Entry}",
  journal = "Science",
  volume  =  208,
  pages   = "1019-1026",
}
@article{hcr:83,
title = {Strategic explanations for a diagnostic consultation system},
journal = {International Journal of Man-Machine Studies},
volume = {20},
number = {1},
pages = {3-19},
year = {1984},
issn = {0020-7373},
doi = {https://doi.org/10.1016/S0020-7373(84)80003-6},
url = {https://www.sciencedirect.com/science/article/pii/S0020737384800036},
author = {Diane Warner Hasling and William J. Clancey and Glenn Rennels},
abstract = {This article examines the problem of automatte explanation of reasoning, especially as it relates to expert systems. By explanation we mean the ability of a program to discuss what it is doing in some understandable way. We first present a general framework in which to view explanation and review some of the research done in this area. We then focus on the explanation system for NEOMYCIN, a medical consultation program. A consultation program interactively helps a user to solve a problem. Our goal is to have NEOMYCIN explain its problem-solving strategies. An explanation of strategy describes the plan the program is using to reach a solution. Such an explanation is usually concrete, referring to aspects of the current problem situation. Abstract explanations articulate a general principle, which can be applied in different situations; such explanations are useful in teaching and in explaining by analogy. We describe the aspects of NEOMYCIN that make abstract strategic explanations possible—the representation of strategic knowledge explicitly and separately from domain knowledge— and demonstrate how this representation can be used to generate explanations.}
}
@article{hcrt:83,
  author  = "Hasling, Diane Warner and Clancey, William J. and Rennels, Glenn R. and Test, Thomas",
  year    = 1983,
  title   = "{Strategic Explanations in Consultation---Duplicate}",
  journal = "The International Journal of Man-Machine Studies",
  volume  = 20,
  number  = 1,
  pages   = "3-19",
}
@techreport{r:86,
  author  = "Rice, James",
  year    = 1986,
  title   = "{Poligon: A System for Parallel Problem Solving}",
  type    = "Technical Report", 
  number  = "KSL-86-19", 
  institution = "Dept.\ of Computer Science, Stanford Univ.",
}
@phdthesis{c:79,
  author  = "Clancey, William J.",
  year    = 1979,
  title   = "{Transfer of Rule-Based Expertise
through a Tutorial Dialogue}",
  type    = "{Ph.D.} diss.",
  school  = "Dept.\ of Computer Science, Stanford Univ.",
  address = "Stanford, Calif.",
}
@unpublished{c:21,
  author  = "Clancey, William J.",
  title   = "{The Engineering of Qualitative Models}",
  year    = 2021,
  note    = "Forthcoming",
}
@misc{c:22,
      title={Crime and punishment in scientific research}, 
      author={Mathieu Bouville},
      year={2008},
      eprint={0803.4058},
      archivePrefix={arXiv},
      primaryClass={physics.soc-ph}
}
@misc{c:23,
  title        = "Pluto: The 'Other' Red Planet",
  author       = "{NASA}",
  howpublished = "\url{https://www.nasa.gov/nh/pluto-the-other-red-planet}",
  year         = 2015,
  note         = "Accessed: 2018-12-06"
}