Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization

26 February 2020

Papers citing "Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization"

6 / 6 papers shown

Title
Improving Adversarial Robustness via Mutual Information Estimation Dawei Zhou Nannan Wang Xinbo Gao Bo Han Xiaoyu Wang Yibing Zhan Tongliang Liu AAML 19 15 0 25 Jul 2022
Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective Jihong Wang Minnan Luo Jundong Li Ziqi Liu Jun Zhou Qinghua Zheng AAML 23 5 0 21 Jan 2022
Unsupervised Adversarially-Robust Representation Learning on Graphs Jiarong Xu Yang Yang Junru Chen Chunping Wang Xin Jiang Jiangang Lu Yizhou Sun SSL AAML OOD 38 36 0 04 Dec 2020
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective Wei Ping Shuohang Wang Yu Cheng Zhe Gan R. Jia Bo-wen Li Jingjing Liu AAML 46 113 0 05 Oct 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 15 92 0 24 Feb 2020
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 65 230 0 25 May 2018