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PAC-learning in the presence of evasion adversaries

5 June 2018

Papers citing "PAC-learning in the presence of evasion adversaries"

42 / 42 papers shown

Title
Strategic Classification with Non-Linear Classifiers Benyamin Trachtenberg Nir Rosenfeld 128 1 0 29 May 2025
On the Computability of Robust PAC LearningAnnual Conference Computational Learning Theory (COLT), 2024 Pascale Gourdeau Tosca Lechner Ruth Urner 343 5 0 14 Jun 2024
Uniformly Stable Algorithms for Adversarial Training and BeyondInternational Conference on Machine Learning (ICML), 2024 Jiancong Xiao Jiawei Zhang Zhimin Luo Asuman Ozdaglar AAML 183 2 0 03 May 2024
Robust optimization for adversarial learning with finite sample complexity guaranteesIEEE Conference on Decision and Control (CDC), 2024 André Bertolace Konstatinos Gatsis Kostas Margellos AAML 127 1 0 22 Mar 2024
On robust overfitting: adversarial training induced distribution matters Runzhi Tian Yongyi Mao OOD 244 1 0 28 Nov 2023
Probably Approximately Correct Federated Learning Xiaojin Zhang Anbu Huang Lixin Fan Kai Chen Qiang Yang FedML 352 5 0 10 Apr 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial RobustnessACM Computing Surveys (ACM Comput. Surv.), 2023 Peiyu Xiong Michael W. Tegegn Jaskeerat Singh Sarin Shubhraneel Pal Julia Rubin SILM AAML 338 14 0 17 Mar 2023
Adversarial Rademacher Complexity of Deep Neural Networks Jiancong Xiao Yanbo Fan Tian Ding Zhimin Luo AAML 121 26 0 27 Nov 2022
When are Local Queries Useful for Robust Learning?Neural Information Processing Systems (NeurIPS), 2022 Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell OOD 327 1 0 12 Oct 2022
Formulating Robustness Against Unforeseen AttacksNeural Information Processing Systems (NeurIPS), 2022 Sihui Dai Saeed Mahloujifar Prateek Mittal OOD AAML 284 9 0 28 Apr 2022
Adversarial robustness of sparse local Lipschitz predictorsSIAM Journal on Mathematics of Data Science (SIMODS), 2022 Ramchandran Muthukumar Jeremias Sulam AAML 225 15 0 26 Feb 2022
A Law of Robustness beyond IsoperimetryInternational Conference on Machine Learning (ICML), 2022 Yihan Wu Heng Huang Hongyang R. Zhang OOD 147 7 0 23 Feb 2022
Probabilistically Robust Learning: Balancing Average- and Worst-case PerformanceInternational Conference on Machine Learning (ICML), 2022 Avi Schwarzschild Luiz F. O. Chamon George J. Pappas Hamed Hassani AAML OOD 347 48 0 02 Feb 2022
Benign Overfitting in Adversarially Robust Linear ClassificationConference on Uncertainty in Artificial Intelligence (UAI), 2021 Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 186 11 0 31 Dec 2021
On the Existence of the Adversarial Bayes Classifier (Extended Version) Pranjal Awasthi Natalie Frank M. Mohri 331 27 0 03 Dec 2021
Adversarial Robustness with Semi-Infinite Constrained LearningNeural Information Processing Systems (NeurIPS), 2021 Avi Schwarzschild Luiz F. O. Chamon George J. Pappas Hamed Hassani Alejandro Ribeiro AAML OOD 277 49 0 29 Oct 2021
Probabilistic Margins for Instance Reweighting in Adversarial TrainingNeural Information Processing Systems (NeurIPS), 2021 Qizhou Wang Yifan Zhang Bo Han Tongliang Liu Chen Gong Gang Niu Mingyuan Zhou Masashi Sugiyama AAML 171 74 0 15 Jun 2021
Calibration and Consistency of Adversarial Surrogate LossesNeural Information Processing Systems (NeurIPS), 2021 Pranjal Awasthi Natalie Frank Anqi Mao M. Mohri Yutao Zhong AAML 195 56 0 19 Apr 2021
Provable Robustness of Adversarial Training for Learning Halfspaces with NoiseInternational Conference on Machine Learning (ICML), 2021 Difan Zou Spencer Frei Quanquan Gu 135 14 0 19 Apr 2021
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition Yaodong Yu Zitong Yang Guang Cheng Jacob Steinhardt Yi-An Ma 238 19 0 17 Mar 2021
Recent Advances in Adversarial Training for Adversarial RobustnessInternational Joint Conference on Artificial Intelligence (IJCAI), 2021 Tao Bai Jinqi Luo Jun Zhao Bihan Wen Qian Wang AAML 409 568 0 02 Feb 2021
With False Friends Like These, Who Can Notice Mistakes?AAAI Conference on Artificial Intelligence (AAAI), 2020 Lue Tao Lei Feng Jinfeng Yi Songcan Chen AAML 301 6 0 29 Dec 2020
Towards Understanding the Regularization of Adversarial Robustness on Neural NetworksInternational Conference on Machine Learning (ICML), 2020 Yuxin Wen Shuai Li Kui Jia AAML 115 25 0 15 Nov 2020
Query complexity of adversarial attacksInternational Conference on Machine Learning (ICML), 2020 Grzegorz Gluch R. Urbanke AAML 182 7 0 02 Oct 2020
Learning to Learn from Mistakes: Robust Optimization for Adversarial NoiseInternational Conference on Artificial Neural Networks (ICANN), 2020 A. Serban E. Poll Joost Visser AAML 143 1 0 12 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive SurveyACM Computing Surveys (ACM CSUR), 2020 A. Serban E. Poll Joost Visser AAML 373 78 0 07 Aug 2020
Provable tradeoffs in adversarially robust classification Guang Cheng Hamed Hassani David Hong Avi Schwarzschild 400 58 0 09 Jun 2020
Towards Deep Learning Models Resistant to Large Perturbations Amirreza Shaeiri Rozhin Nobahari M. Rohban OOD AAML 151 14 0 30 Mar 2020
Adversarial VC-dimension and Sample Complexity of Neural Networks Zetong Qi T. J. Wilder AAML 45 0 0 18 Dec 2019
Adversarially Robust Low Dimensional RepresentationsAnnual Conference Computational Learning Theory (COLT), 2019 Pranjal Awasthi Vaggos Chatziafratis Xue Chen Aravindan Vijayaraghavan AAML OOD 298 12 0 29 Nov 2019
On Robustness to Adversarial Examples and Polynomial OptimizationNeural Information Processing Systems (NeurIPS), 2019 Pranjal Awasthi Abhratanu Dutta Aravindan Vijayaraghavan OOD AAML 156 34 0 12 Nov 2019
The Adversarial Robustness of SamplingIACR Cryptology ePrint Archive (IACR ePrint), 2019 Omri Ben-Eliezer E. Yogev TTA AAML 123 54 0 26 Jun 2019
Lower Bounds for Adversarially Robust PAC LearningInternational Conference on Machine Learning and Applications (ICMLA), 2019 Dimitrios I. Diochnos Saeed Mahloujifar Mohammad Mahmoody AAML 208 27 0 13 Jun 2019
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression E. Balda Arash Behboodi Niklas Koep R. Mathar AAML 149 9 0 03 Jun 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He John E. Hopcroft Liwei Wang 193 160 0 03 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete DataNeural Information Processing Systems (NeurIPS), 2019 Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 179 135 0 24 May 2019
VC Classes are Adversarially Robustly Learnable, but Only ImproperlyAnnual Conference Computational Learning Theory (COLT), 2019 Omar Montasser Steve Hanneke Nathan Srebro 234 145 0 12 Feb 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 169 153 0 15 Jan 2019
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 126 71 0 13 Nov 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin Kannan Ramchandran Peter L. Bartlett AAML 323 278 0 29 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 196 49 0 02 Oct 2018
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker Matej Moravcík Martin Schmid Neil Burch Viliam Lisý Dustin Morrill Nolan Bard Trevor Davis Kevin Waugh Michael Bradley Johanson Michael Bowling BDL 548 959 0 06 Jan 2017