Robustness to Adversarial Perturbations in Learning from Incomplete Data

24 May 2019

Papers citing "Robustness to Adversarial Perturbations in Learning from Incomplete Data"

50 / 81 papers shown

Title
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Naome A. Etori Maria Gini 81 2 0 10 Feb 2025
Improving the Efficiency of Self-Supervised Adversarial Training through Latent Clustering-Based Selection Somrita Ghosh Yuelin Xu Xiao Zhang AAML OOD 55 0 0 15 Jan 2025
New Paradigm of Adversarial Training: Breaking Inherent Trade-Off between Accuracy and Robustness via Dummy Classes Yufei Wang Li Liu Zi Liang Qingqing Ye Haibo Hu AAML 23 1 0 16 Oct 2024
NPAT Null-Space Projected Adversarial Training Towards Zero Deterioration Hanyi Hu Qiao Han Kui Chen Yao Yang AAML 33 0 0 18 Sep 2024
Deep Learning with Data Privacy via Residual Perturbation Wenqi Tao Huaming Ling Zuoqiang Shi Bao Wang 21 2 0 11 Aug 2024
Towards unlocking the mystery of adversarial fragility of neural networks Jingchao Gao Raghu Mudumbai Xiaodong Wu Jirong Yi Catherine Xu Hui Xie Weiyu Xu 35 1 0 23 Jun 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 26 0 0 26 Jan 2024
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training Shruthi Gowda Bahram Zonooz Elahe Arani AAML 31 2 0 26 Jan 2024
Understanding and Improving Ensemble Adversarial Defense Yian Deng Tingting Mu AAML 24 19 0 27 Oct 2023
Out-Of-Domain Unlabeled Data Improves Generalization Amir Saberi Amir Najafi Alireza Heidari Mohammad Hosein Movasaghinia Abolfazl Motahari B. Khalaj OOD 21 0 0 29 Sep 2023
Noisy Self-Training with Data Augmentations for Offensive and Hate Speech Detection Tasks João A. Leite Carolina Scarton D. F. Silva 45 1 0 31 Jul 2023
Adversarial Training with Generated Data in High-Dimensional Regression: An Asymptotic Study Yue Xing 22 0 0 21 Jun 2023
Generalist: Decoupling Natural and Robust Generalization Hongjun Wang Yisen Wang OOD AAML 49 14 0 24 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 32 8 0 17 Mar 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min Lin Weiwei Liu Shuicheng Yan DiffM 26 208 0 09 Feb 2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness Yuancheng Xu Yanchao Sun Micah Goldblum Tom Goldstein Furong Huang AAML 31 37 0 06 Feb 2023
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks Jianan Zhou Jianing Zhu Jingfeng Zhang Tongliang Liu Gang Niu Bo Han Masashi Sugiyama AAML 11 9 0 01 Nov 2022
Denoising Masked AutoEncoders Help Robust Classification Quanlin Wu Hang Ye Yuntian Gu Huishuai Zhang Liwei Wang Di He 14 21 0 10 Oct 2022
Semi-Supervised and Unsupervised Deep Visual Learning: A Survey Yanbei Chen Massimiliano Mancini Xiatian Zhu Zeynep Akata 45 113 0 24 Aug 2022
Why is the video analytics accuracy fluctuating, and what can we do about it? Sibendu Paul Kunal Rao G. Coviello Murugan Sankaradas Oliver Po Y. C. Hu S. Chakradhar AAML 14 3 0 23 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
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness Chaoning Zhang Kang Zhang Chenshuang Zhang Axi Niu Jiu Feng Chang D. Yoo In So Kweon SSL 40 24 0 22 Jul 2022
Global-Local Regularization Via Distributional Robustness Hoang Phan Trung Le Trung-Nghia Phung Tu Bui Nhat Ho Dinh Q. Phung OOD 22 12 0 01 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 39 42 0 27 Feb 2022
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness Yue Xing Qifan Song Guang Cheng 14 4 0 14 Feb 2022
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability Idan Attias Steve Hanneke Yishay Mansour 35 15 0 11 Feb 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 212 345 0 15 Dec 2021
Assessing Fairness in the Presence of Missing Data Yiliang Zhang Q. Long FaML 31 35 0 07 Dec 2021
Data Augmentation Can Improve Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 34 270 0 09 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 43 17 0 09 Nov 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 36 294 0 18 Oct 2021
Bridged Adversarial Training Hoki Kim Woojin Lee Sungyoon Lee Jaewook Lee AAML GAN 21 9 0 25 Aug 2021
Distributionally Robust Learning Ruidi Chen I. Paschalidis OOD 25 65 0 20 Aug 2021
CausalAdv: Adversarial Robustness through the Lens of Causality Yonggang Zhang Biwei Huang Tongliang Liu Gang Niu Xinmei Tian Bo Han Bernhard Schölkopf Kun Zhang OOD AAML CML 27 35 0 11 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 23 9 0 31 May 2021
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? Vikash Sehwag Saeed Mahloujifar Tinashe Handina Sihui Dai Chong Xiang M. Chiang Prateek Mittal OOD 47 127 0 19 Apr 2021
Achieving Transparency Report Privacy in Linear Time Chien-Lun Chen L. Golubchik R. Pal 11 2 0 31 Mar 2021
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition Yaodong Yu Zitong Yang Yan Sun Jacob Steinhardt Yi Ma 18 17 0 17 Mar 2021
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN Desheng Wang Wei-dong Jin Yunpu Wu Aamir Khan GAN 36 8 0 08 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 36 270 0 02 Mar 2021
Explaining Adversarial Vulnerability with a Data Sparsity Hypothesis Mahsa Paknezhad Cuong Phuc Ngo Amadeus Aristo Winarto Alistair Cheong Beh Chuen Yang Wu Jiayang Lee Hwee Kuan OOD AAML 29 9 0 01 Mar 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 32 10 0 15 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao Bihan Wen Qian Wang AAML 86 476 0 02 Feb 2021
Removing Undesirable Feature Contributions Using Out-of-Distribution Data Saehyung Lee Changhwa Park Hyungyu Lee Jihun Yi Jonghyun Lee Sungroh Yoon OODD 11 24 0 17 Jan 2021
Adversarially Robust Estimate and Risk Analysis in Linear Regression Yue Xing Ruizhi Zhang Guang Cheng AAML 28 27 0 18 Dec 2020
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness Sang Michael Xie Ananya Kumar Robbie Jones Fereshte Khani Tengyu Ma Percy Liang OOD 174 62 0 08 Dec 2020
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately Fereshte Khani Percy Liang FaML 21 65 0 07 Dec 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach Haoxu Wang Zhiding Yu Yisong Yue Anima Anandkumar Anqi Liu Junchi Yan OOD UQCV 13 4 0 08 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 324 0 07 Oct 2020