Reliable learning in challenging environments

6 April 2023

Papers citing "Reliable learning in challenging environments"

50 / 54 papers shown

Title
On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space Yuyang Deng Nidham Gazagnadou Junyuan Hong M. Mahdavi Lingjuan Lyu AAML 24 5 0 23 Feb 2023
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games Maria-Florina Balcan Rattana Pukdee Pradeep Ravikumar Hongyang R. Zhang AAML 49 12 0 23 Oct 2022
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization Omar Montasser Steve Hanneke Nathan Srebro 66 17 0 15 Sep 2022
Robustly-reliable learners under poisoning attacks Maria-Florina Balcan Avrim Blum Steve Hanneke Dravyansh Sharma AAML OOD 51 14 0 08 Mar 2022
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation Wenxiao Wang Alexander Levine Soheil Feizi AAML 59 60 0 05 Feb 2022
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization John Miller Rohan Taori Aditi Raghunathan Shiori Sagawa Pang Wei Koh Vaishaal Shankar Percy Liang Y. Carmon Ludwig Schmidt OODD OOD 67 276 0 09 Jul 2021
Adversarially Robust Learning with Unknown Perturbation Sets Omar Montasser Steve Hanneke Nathan Srebro AAML 60 27 0 03 Feb 2021
Exponential Savings in Agnostic Active Learning through Abstention Nikita Puchkin Nikita Zhivotovskiy 54 20 0 31 Jan 2021
Reducing Adversarially Robust Learning to Non-Robust PAC Learning Omar Montasser Steve Hanneke Nathan Srebro 70 31 0 22 Oct 2020
The Risks of Invariant Risk Minimization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 74 311 0 12 Oct 2020
Noise in Classification Maria-Florina Balcan Nika Haghtalab 26 11 0 10 Oct 2020
On Localized Discrepancy for Domain Adaptation Yuchen Zhang Mingsheng Long Jianmin Wang Michael I. Jordan 54 18 0 14 Aug 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 62 424 0 16 Jul 2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples S. Goldwasser Adam Tauman Kalai Y. Kalai Omar Montasser AAML 45 40 0 10 Jul 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 94 801 0 26 Feb 2020
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang AAML 82 228 0 25 Feb 2020
Precise Tradeoffs in Adversarial Training for Linear Regression Adel Javanmard Mahdi Soltanolkotabi Hamed Hassani AAML 50 107 0 24 Feb 2020
On the Value of Target Data in Transfer Learning Steve Hanneke Samory Kpotufe 50 74 0 12 Feb 2020
Noise-tolerant, Reliable Active Classification with Comparison Queries Max Hopkins D. Kane Shachar Lovett G. Mahajan AAML NoLa 33 26 0 15 Jan 2020
On the Hardness of Robust Classification Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell 42 43 0 12 Sep 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 177 2,222 0 05 Jul 2019
Distribution-Independent PAC Learning of Halfspaces with Massart Noise Ilias Diakonikolas Themis Gouleakis Christos Tzamos 70 82 0 24 Jun 2019
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao Colin Wei Adrien Gaidon Nikos Arechiga Tengyu Ma 113 1,600 0 18 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 121 752 0 31 May 2019
Adversarially robust transfer learning Ali Shafahi Parsa Saadatpanah Chen Zhu Amin Ghiasi Christoph Studer David Jacobs Tom Goldstein OOD 44 116 0 20 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 125 1,247 0 29 Apr 2019
Bridging Theory and Algorithm for Domain Adaptation Yuchen Zhang Tianle Liu Mingsheng Long Michael I. Jordan 78 710 0 11 Apr 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 66 75 0 25 Mar 2019
Do ImageNet Classifiers Generalize to ImageNet? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD SSeg VLM 111 1,714 0 13 Feb 2019
VC Classes are Adversarially Robustly Learnable, but Only Improperly Omar Montasser Steve Hanneke Nathan Srebro 29 139 0 12 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 139 2,038 0 08 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 82 807 0 07 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 129 2,548 0 24 Jan 2019
Learning Models with Uniform Performance via Distributionally Robust Optimization John C. Duchi Hongseok Namkoong OOD 55 417 0 20 Oct 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 91 348 0 10 Sep 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 99 1,778 0 30 May 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar Aleksander Madry OOD AAML 131 790 0 30 Apr 2018
Detecting and Correcting for Label Shift with Black Box Predictors Zachary Chase Lipton Yu Wang Alex Smola OOD 58 553 0 12 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 92 932 0 09 Feb 2018
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 299 12,060 0 19 Jun 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 291 5,825 0 14 Jun 2017
Certified Defenses for Data Poisoning Attacks Jacob Steinhardt Pang Wei Koh Percy Liang AAML 83 754 0 09 Jun 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,725 0 19 May 2017
Online Learning with Abstention Corinna Cortes Giulia DeSalvo Claudio Gentile M. Mohri Scott Yang 97 47 0 09 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 820 5,806 0 05 Dec 2016
Active Learning from Imperfect Labelers Songbai Yan Kamalika Chaudhuri T. Javidi 49 55 0 30 Oct 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 256 8,550 0 16 Aug 2016
Deep CORAL: Correlation Alignment for Deep Domain Adaptation Baochen Sun Kate Saenko OOD 100 3,151 0 06 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 813 9,302 0 06 Jun 2015
Complexity Theoretic Limitations on Learning Halfspaces Amit Daniely 103 139 0 21 May 2015