Adversarially Robust Generalization Requires More Data

30 April 2018

Papers citing "Adversarially Robust Generalization Requires More Data"

50 / 198 papers shown

Title
When to retrain a machine learning model Regol Florence Schwinn Leo Sprague Kyle Coates Mark Markovich Thomas OffRL 9 0 0 20 May 2025
Risk Analysis and Design Against Adversarial Actions M. Campi A. Carè Luis G. Crespo S. Garatti Federico A. Ramponi AAML 204 0 0 02 May 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs Kasimir Tanner Matteo Vilucchio Bruno Loureiro Florent Krzakala AAML 63 0 0 31 Dec 2024
Robust Feature Learning for Multi-Index Models in High Dimensions Alireza Mousavi-Hosseini Adel Javanmard Murat A. Erdogdu OOD AAML 51 1 0 21 Oct 2024
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 35 2 0 09 Oct 2024
Mitigating Memorization In Language Models Mansi Sakarvadia Aswathy Ajith Arham Khan Nathaniel Hudson Caleb Geniesse Kyle Chard Yaoqing Yang Ian Foster Michael W. Mahoney KELM MU 58 1 0 03 Oct 2024
Evaluating Model Robustness Using Adaptive Sparse L0 Regularization Weiyou Liu Zhenyang Li Weitong Chen AAML 30 1 0 28 Aug 2024
Adversarial Robustification via Text-to-Image Diffusion Models Daewon Choi Jongheon Jeong Huiwon Jang Jinwoo Shin DiffM 47 1 0 26 Jul 2024
MEAT: Median-Ensemble Adversarial Training for Improving Robustness and Generalization Zhaozhe Hu Jia-Li Yin Bin Chen Luojun Lin Bo-Hao Chen Ximeng Liu AAML 35 0 0 20 Jun 2024
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness Maayan Ehrenberg Roy Ganz Nir Rosenfeld AAML 56 0 0 17 Jun 2024
Exploiting the Layered Intrinsic Dimensionality of Deep Models for Practical Adversarial Training Enes Altinisik Safa Messaoud Husrev Taha Sencar Hassan Sajjad Sanjay Chawla AAML 53 0 0 27 May 2024
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective Nils Philipp Walter Linara Adilova Jilles Vreeken Michael Kamp AAML 51 2 0 27 May 2024
Uniformly Stable Algorithms for Adversarial Training and Beyond Jiancong Xiao Jiawei Zhang Zhimin Luo Asuman Ozdaglar AAML 48 0 0 03 May 2024
From Robustness to Improved Generalization and Calibration in Pre-trained Language Models Josip Jukić Jan Snajder 53 0 0 31 Mar 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
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training Shruthi Gowda Bahram Zonooz Elahe Arani AAML 36 2 0 26 Jan 2024
Rethinking Adversarial Training with Neural Tangent Kernel Guanlin Li Han Qiu Shangwei Guo Jiwei Li Tianwei Zhang AAML 29 0 0 04 Dec 2023
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off Yatong Bai Brendon G. Anderson Somayeh Sojoudi AAML 35 2 0 26 Nov 2023
On The Relationship Between Universal Adversarial Attacks And Sparse Representations Dana Weitzner Raja Giryes AAML 32 0 0 14 Nov 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao Rene Vidal 28 8 0 28 Sep 2023
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees Ali Ramezani-Kebrya Kimon Antonakopoulos Igor Krawczuk Justin Deschenaux V. Cevher 41 3 0 17 Aug 2023
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms Elvis Dohmatob M. Scetbon AAML OOD 28 0 0 01 Aug 2023
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness Jovon Craig Joshua Andle Theodore S. Nowak Salimeh Yasaei Sekeh AAML 53 0 0 07 Jul 2023
On the Importance of Backbone to the Adversarial Robustness of Object Detectors Xiao-Li Li Hang Chen Xiaolin Hu AAML 54 4 0 27 May 2023
Fantastic DNN Classifiers and How to Identify them without Data Nathaniel R. Dean D. Sarkar 23 1 0 24 May 2023
Reliable learning in challenging environments Maria-Florina Balcan Steve Hanneke Rattana Pukdee Dravyansh Sharma OOD 30 4 0 06 Apr 2023
Probing the Purview of Neural Networks via Gradient Analysis Jinsol Lee Charles Lehman Mohit Prabhushankar Ghassan AlRegib 34 7 0 06 Apr 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Wei Wei Jiahuan Zhou Yingying Wu AAML 20 0 0 29 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 44 34 0 19 Mar 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness Peiyu Xiong Michael W. Tegegn Jaskeerat Singh Sarin Shubhraneel Pal Julia Rubin SILM AAML 37 8 0 17 Mar 2023
Certified Robust Neural Networks: Generalization and Corruption Resistance Amine Bennouna Ryan Lucas Bart P. G. Van Parys 48 10 0 03 Mar 2023
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker Sihui Dai Wen-Luan Ding A. Bhagoji Daniel Cullina Ben Y. Zhao Haitao Zheng Prateek Mittal AAML 37 2 0 21 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min Lin Weiwei Liu Shuicheng Yan DiffM 26 210 0 09 Feb 2023
Linking convolutional kernel size to generalization bias in face analysis CNNs Hao Liang J. O. Caro Vikram Maheshri Ankit B. Patel Guha Balakrishnan CVBM CML 23 0 0 07 Feb 2023
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks Salah Ghamizi Jingfeng Zhang Maxime Cordy Mike Papadakis Masashi Sugiyama Yves Le Traon AAML 36 2 0 06 Feb 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 41 18 0 29 Jan 2023
Data Augmentation Alone Can Improve Adversarial Training Lin Li Michael W. Spratling 21 50 0 24 Jan 2023
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability Chengtai Cao Fan Zhou Yurou Dai Jianping Wang Kunpeng Zhang AAML 31 28 0 21 Dec 2022
Foundation models in brief: A historical, socio-technical focus Johannes Schneider VLM 31 9 0 17 Dec 2022
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 29 5 0 15 Dec 2022
Malign Overfitting: Interpolation Can Provably Preclude Invariance Yoav Wald G. Yona Uri Shalit Y. Carmon 19 6 0 28 Nov 2022
Adversarial Rademacher Complexity of Deep Neural Networks Jiancong Xiao Yanbo Fan Ruoyu Sun Zhimin Luo AAML 22 22 0 27 Nov 2022
Adversarial Detection by Approximation of Ensemble Boundary T. Windeatt AAML 26 0 0 18 Nov 2022
Textual Manifold-based Defense Against Natural Language Adversarial Examples D. M. Nguyen Anh Tuan Luu AAML 27 17 0 05 Nov 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 44 13 0 21 Oct 2022
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation Jun-Kun Wang Andre Wibisono 37 7 0 18 Oct 2022
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors Qixun Wang Yifei Wang Hong Zhu Yisen Wang OOD 22 19 0 13 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 38 30 0 03 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 39 7 0 02 Oct 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training Saehyung Lee Hyungyu Lee AAML 29 2 0 27 Sep 2022