Rademacher Complexity for Adversarially Robust Generalization

29 October 2018

Papers citing "Rademacher Complexity for Adversarially Robust Generalization"

50 / 55 papers shown

Title
Wasserstein Distributionally Robust Nonparametric Regression Changyu Liu Yuling Jiao Junhui Wang Jian Huang OOD 31 0 0 12 May 2025
Risk Analysis and Design Against Adversarial Actions M. Campi A. Carè Luis G. Crespo S. Garatti Federico A. Ramponi AAML 127 0 0 02 May 2025
DONOD: Robust and Generalizable Instruction Fine-Tuning for LLMs via Model-Intrinsic Dataset Pruning Jucheng Hu S. M. I. Simon X. Yang Dongzhan Zhou Lijun Wu 34 0 0 21 Apr 2025
Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home Viktor Moskvoretskii M. Lysyuk Mikhail Salnikov Nikolay Ivanov Sergey Pletenev Daria Galimzianova Nikita Krayko Vasily Konovalov Irina Nikishina Alexander Panchenko RALM 74 4 0 24 Feb 2025
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization Dun Zeng Zheshun Wu Shiyu Liu Yu Pan Xiaoying Tang Zenglin Xu MLT FedML 89 1 0 25 Nov 2024
Efficient Optimization Algorithms for Linear Adversarial Training Antônio H. Ribeiro Thomas B. Schon Dave Zahariah Francis Bach AAML 45 1 0 16 Oct 2024
Uniformly Stable Algorithms for Adversarial Training and Beyond Jiancong Xiao Jiawei Zhang Zhimin Luo Asuman Ozdaglar AAML 45 0 0 03 May 2024
$Asymptotic Behavior of Adversarial Training Estimator under $\ell_\infty$-Perturbation$ Asymptotic Behavior of Adversarial Training Estimator under $\ell_\infty$ -Perturbation Yiling Xie Xiaoming Huo 36 2 0 27 Jan 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective Yue Xing Xiaofeng Lin Qifan Song Yi Tian Xu Belinda Zeng Guang Cheng SSL 23 0 0 26 Jan 2024
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization Jiancong Xiao Ruoyu Sun Zhimin Luo AAML 32 6 0 09 Oct 2023
Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression Junho Kim Byung-Kwan Lee Yonghyun Ro CML AAML 20 18 0 02 Mar 2023
AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputs Helene Orsini Hongyan Bao Yujun Zhou Xiangrui Xu Yufei Han Longyang Yi Wei Wang Xin Gao Xiangliang Zhang AAML 21 1 0 13 Dec 2022
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 34 3 0 08 Dec 2022
When are Local Queries Useful for Robust Learning? Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell OOD 35 1 0 12 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 29 30 0 03 Oct 2022
Robust Empirical Risk Minimization with Tolerance Robi Bhattacharjee Max Hopkins Akash Kumar Hantao Yu Kamalika Chaudhuri OOD 28 8 0 02 Oct 2022
Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability Analysis Jiancong Xiao Zeyu Qin Yanbo Fan Baoyuan Wu Jue Wang Zhimin Luo AAML 31 7 0 02 Oct 2022
On the Role of Generalization in Transferability of Adversarial Examples Yilin Wang Farzan Farnia AAML 24 10 0 18 Jun 2022
The Consistency of Adversarial Training for Binary Classification Natalie Frank Jonathan Niles-Weed AAML 33 5 0 18 Jun 2022
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 45 15 0 07 Jun 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 27 13 0 22 Mar 2022
Robustly-reliable learners under poisoning attacks Maria-Florina Balcan Avrim Blum Steve Hanneke Dravyansh Sharma AAML OOD 26 14 0 08 Mar 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 13 18 0 03 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability Idan Attias Steve Hanneke Yishay Mansour 30 15 0 11 Feb 2022
An Exploration of Multicalibration Uniform Convergence Bounds Harrison Rosenberg Robi Bhattacharjee Kassem Fawaz S. Jha 14 1 0 09 Feb 2022
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 31 10 0 31 Dec 2021
On the Existence of the Adversarial Bayes Classifier (Extended Version) Pranjal Awasthi Natalie Frank M. Mohri 26 24 0 03 Dec 2021
Transductive Robust Learning Guarantees Omar Montasser Steve Hanneke Nathan Srebro 16 13 0 20 Oct 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 36 1 0 27 Sep 2021
Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models Kun Zhou Wayne Xin Zhao Sirui Wang Fuzheng Zhang Wei Yu Wu Ji-Rong Wen AAML 21 7 0 13 Sep 2021
Regional Adversarial Training for Better Robust Generalization Chuanbiao Song Yanbo Fan Yichen Yang Baoyuan Wu Yiming Li Zhifeng Li Kun He AAML OOD 13 6 0 02 Sep 2021
Attack Transferability Characterization for Adversarially Robust Multi-label Classification Zhuo Yang Yufei Han Xiangliang Zhang AAML 23 4 0 29 Jun 2021
Improved OOD Generalization via Adversarial Training and Pre-training Mingyang Yi Lu Hou Jiacheng Sun Lifeng Shang Xin Jiang Qun Liu Zhi-Ming Ma VLM 23 83 0 24 May 2021
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip H. S. Torr NoLa AAML 23 57 0 08 Jul 2020
A Le Cam Type Bound for Adversarial Learning and Applications Qiuling Xu Kevin Bello Jean Honorio AAML 16 1 0 01 Jul 2020
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification Chen Dan Yuting Wei Pradeep Ravikumar 24 45 0 29 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels Jun Shu Qian Zhao Zengben Xu Deyu Meng NoLa 31 29 0 10 Jun 2020
Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity Nam Ho-Nguyen Stephen J. Wright OOD 40 16 0 28 May 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 22 29 0 17 May 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise Omar Montasser Surbhi Goel Ilias Diakonikolas Nathan Srebro 29 32 0 15 May 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi Natalie Frank M. Mohri AAML 28 56 0 28 Apr 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 30 785 0 26 Feb 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang Xilie Xu Bo Han Gang Niu Li-zhen Cui Masashi Sugiyama Mohan S. Kankanhalli AAML 22 396 0 26 Feb 2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min Lin Chen Amin Karbasi AAML 31 69 0 25 Feb 2020
MaxUp: A Simple Way to Improve Generalization of Neural Network Training Chengyue Gong Tongzheng Ren Mao Ye Qiang Liu AAML 19 56 0 20 Feb 2020
CAT: Customized Adversarial Training for Improved Robustness Minhao Cheng Qi Lei Pin-Yu Chen Inderjit Dhillon Cho-Jui Hsieh OOD AAML 24 114 0 17 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 27 64 0 11 Feb 2020
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 36 85 0 09 Oct 2019
Adversarial Training Can Hurt Generalization Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang 13 239 0 14 Jun 2019