Data Augmentation Can Improve Robustness

9 November 2021

Sylvestre-Alvise Rebuffi

Papers citing "Data Augmentation Can Improve Robustness"

50 / 154 papers shown

Title
Steerable Equivariant Representation Learning Sangnie Bhardwaj Willie McClinton Tongzhou Wang Guillaume Lajoie Chen Sun Phillip Isola Dilip Krishnan OOD LLMSV 34 5 0 22 Feb 2023
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts Francesco Croce Sylvestre-Alvise Rebuffi Evan Shelhamer Sven Gowal AAML 42 17 0 20 Feb 2023
Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition Luke E. Richards Edward Raff Cynthia Matuszek AAML 16 2 0 17 Feb 2023
HateProof: Are Hateful Meme Detection Systems really Robust? Piush Aggarwal Pranit Chawla Mithun Das Punyajoy Saha Binny Mathew Torsten Zesch Animesh Mukherjee AAML 37 8 0 11 Feb 2023
Toward Degree Bias in Embedding-Based Knowledge Graph Completion Harry Shomer Wei Jin Wentao Wang Jiliang Tang 9 21 0 10 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 28 2 0 06 Feb 2023
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics Jiacheng Zhu Jielin Qiu Aritra Guha Zhuolin Yang X. Nguyen Bo-wen Li Ding Zhao OOD 34 2 0 04 Feb 2023
On Robustness of Prompt-based Semantic Parsing with Large Pre-trained Language Model: An Empirical Study on Codex Terry Yue Zhuo Zhuang Li Yujin Huang Fatemeh Shiri Weiqing Wang Gholamreza Haffari Yuan-Fang Li AAML 34 54 0 30 Jan 2023
A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection Mohammad Azizmalayeri Arman Zarei Alireza Isavand M. T. Manzuri M. Rohban OODD 35 0 0 25 Jan 2023
Data Augmentation Alone Can Improve Adversarial Training Lin Li Michael W. Spratling 16 50 0 24 Jan 2023
Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective Shihua Huang Zhichao Lu Kalyanmoy Deb Vishnu Boddeti OOD 24 41 0 21 Dec 2022
Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural Networks Xiao-Li Li Ziqi Wang Bo-Wen Zhang Gang Hua Xiaolin Hu 32 25 0 04 Dec 2022
Feature Weaken: Vicinal Data Augmentation for Classification Songhao Jiang Yan Chu Tian-Hui Ma Tianning Zang 28 0 0 20 Nov 2022
Scalar Invariant Networks with Zero Bias Chuqin Geng Xiaojie Xu Haolin Ye X. Si 26 1 0 15 Nov 2022
MORA: Improving Ensemble Robustness Evaluation with Model-Reweighing Attack Yunrui Yu Xitong Gao Chengzhong Xu AAML 36 8 0 15 Nov 2022
Scoring Black-Box Models for Adversarial Robustness Jian Vora Pranay Reddy Samala 33 0 0 31 Oct 2022
Efficient and Effective Augmentation Strategy for Adversarial Training Sravanti Addepalli Samyak Jain R. Venkatesh Babu AAML 78 58 0 27 Oct 2022
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games Maria-Florina Balcan Rattana Pukdee Pradeep Ravikumar Hongyang R. Zhang AAML 39 12 0 23 Oct 2022
Learning Sample Reweighting for Accuracy and Adversarial Robustness Chester Holtz Tsui-Wei Weng Gal Mishne OOD 30 4 0 20 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 30 5 0 11 Oct 2022
Revisiting adapters with adversarial training Sylvestre-Alvise Rebuffi Francesco Croce Sven Gowal AAML 36 16 0 10 Oct 2022
Learning Robust Kernel Ensembles with Kernel Average Pooling P. Bashivan Adam Ibrahim Amirozhan Dehghani Yifei Ren OOD 24 5 0 30 Sep 2022
Exploring the Relationship between Architecture and Adversarially Robust Generalization Aishan Liu Shiyu Tang Siyuan Liang Ruihao Gong Boxi Wu Xianglong Liu Dacheng Tao AAML 34 18 0 28 Sep 2022
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 32 68 0 15 Sep 2022
On the interplay of adversarial robustness and architecture components: patches, convolution and attention Francesco Croce Matthias Hein 43 6 0 14 Sep 2022
Bag of Tricks for FGSM Adversarial Training Zichao Li Li Liu Zeyu Wang Yuyin Zhou Cihang Xie AAML 33 6 0 06 Sep 2022
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective Chanwoo Park Sangdoo Yun Sanghyuk Chun AAML 21 32 0 21 Aug 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models Dong Huang Qi Bu Yuhao Qing Haowen Pi Sen Wang Heming Cui OOD AAML 32 0 0 17 Aug 2022
GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction Jiacheng Zhu Jielin Qiu Zhuolin Yang Douglas Weber M. Rosenberg Emerson Liu Bo-wen Li Ding Zhao OOD 28 13 0 02 Aug 2022
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 36 16 0 28 Jun 2022
OOD Augmentation May Be at Odds with Open-Set Recognition Mohammad Azizmalayeri M. Rohban 22 9 0 09 Jun 2022
Wavelet Regularization Benefits Adversarial Training Jun Yan Huilin Yin Xiaoyang Deng Zi-qin Zhao Wancheng Ge Hao Zhang Gerhard Rigoll AAML 19 2 0 08 Jun 2022
Towards Understanding and Mitigating Audio Adversarial Examples for Speaker Recognition Guangke Chen Zhe Zhao Fu Song Sen Chen Lingling Fan Feng Wang Jiashui Wang AAML 20 36 0 07 Jun 2022
Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples Dongyoon Yang Insung Kong Yongdai Kim OOD AAML 15 9 0 07 Jun 2022
FACM: Intermediate Layer Still Retain Effective Features against Adversarial Examples Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 36 0 0 02 Jun 2022
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks Sizhe Chen Zhehao Huang Qinghua Tao Yingwen Wu Cihang Xie X. Huang AAML 110 28 0 24 May 2022
Visual Attention Emerges from Recurrent Sparse Reconstruction Baifeng Shi Ya-heng Song Neel Joshi Trevor Darrell Xin Wang 3DH 22 6 0 23 Apr 2022
A Comprehensive Survey on Data-Efficient GANs in Image Generation Ziqiang Li Beihao Xia Jing Zhang Chaoyue Wang Bin Li 19 33 0 18 Apr 2022
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning Mathias Lechner Alexander Amini Daniela Rus T. Henzinger AAML 29 9 0 15 Apr 2022
StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Translation Peter Schaldenbrand Zhixuan Liu Jean Oh CLIP 35 44 0 24 Feb 2022
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests Xilie Xu Jingfeng Zhang Feng Liu Masashi Sugiyama Mohan S. Kankanhalli AAML 30 1 0 07 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 32 4 0 03 Feb 2022
Hyperparameter Optimization for COVID-19 Chest X-Ray Classification I. Hamdi Muhammad Ridzuan Mohammad Yaqub LM&MA 119 0 0 26 Jan 2022
Improving Robustness with Image Filtering M. Terzi Mattia Carletti Gian Antonio Susto AAML 29 0 0 21 Dec 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 35 4 0 16 Sep 2021
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples Maura Pintor Luca Demetrio Angelo Sotgiu Ambra Demontis Nicholas Carlini Battista Biggio Fabio Roli AAML 28 28 0 18 Jun 2021
Adversarial Robustness against Multiple and Single $l_p$ -Threat Models via Quick Fine-Tuning of Robust Classifiers Francesco Croce Matthias Hein OOD AAML 28 18 0 26 May 2021
Domain Invariant Adversarial Learning Matan Levi Idan Attias A. Kontorovich AAML OOD 37 11 0 01 Apr 2021
Lagrangian Objective Function Leads to Improved Unforeseen Attack Generalization in Adversarial Training Mohammad Azizmalayeri M. Rohban OOD 32 4 0 29 Mar 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 41 57 0 08 Mar 2021