Learning to Defend by Learning to Attack

Learning to Defend by Learning to Attack

3 November 2018

Zhehui Chen

Papers citing "Learning to Defend by Learning to Attack"

18 / 18 papers shown

Title
Make Optimization Once and for All with Fine-grained Guidance Mingjia Shi Ruihan Lin Xuxi Chen Yuhao Zhou Zezhen Ding ... Tong Wang Kai Wang Zhangyang Wang Jun Zhang Tianlong Chen 55 1 0 14 Mar 2025
On Penalty-based Bilevel Gradient Descent Method Han Shen Quan-Wu Xiao Tianyi Chen 60 51 0 08 Jan 2025
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF Han Shen Zhuoran Yang Tianyi Chen OffRL 40 14 0 10 Feb 2024
Stochastic Unrolled Federated Learning Samar Hadou Navid Naderializadeh Alejandro Ribeiro FedML 30 5 0 24 May 2023
Differentiable Arbitrating in Zero-sum Markov Games Jing Wang Meichen Song Feng Gao Boyi Liu Zhaoran Wang Yi Wu 40 2 0 20 Feb 2023
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach Mao Ye B. Liu S. Wright Peter Stone Qian Liu 72 82 0 19 Sep 2022
Gradient-based Bi-level Optimization for Deep Learning: A Survey Can Chen Xiangshan Chen Chen Ma Zixuan Liu Xue Liu 94 35 0 24 Jul 2022
Neur2SP: Neural Two-Stage Stochastic Programming Justin Dumouchelle R. Patel Elias Boutros Khalil Merve Bodur 61 27 0 20 May 2022
Robust Unlearnable Examples: Protecting Data Against Adversarial Learning Shaopeng Fu Fengxiang He Yang Liu Li Shen Dacheng Tao 24 24 0 28 Mar 2022
The Many Faces of Adversarial Risk Muni Sreenivas Pydi Varun Jog AAML 48 29 0 22 Jan 2022
Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness Xiao Yang Yinpeng Dong Wenzhao Xiang Tianyu Pang Hang Su Jun Zhu AAML 27 4 0 13 Oct 2021
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence Boyi Liu Jiayang Li Zhuoran Yang Hoi-To Wai Mingyi Hong Y. Nie Zhaoran Wang 66 18 0 04 Oct 2021
Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems Tommaso Giovannelli G. Kent Luis Nunes Vicente 33 12 0 01 Oct 2021
ARCH: Efficient Adversarial Regularized Training with Caching Simiao Zuo Chen Liang Haoming Jiang Pengcheng He Xiaodong Liu Jianfeng Gao Weizhu Chen T. Zhao AAML 28 3 0 15 Sep 2021
Robustness-via-Synthesis: Robust Training with Generative Adversarial Perturbations Inci M. Baytas Debayan Deb AAML 16 7 0 22 Aug 2021
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach Simiao Zuo Chen Liang Haoming Jiang Xiaodong Liu Pengcheng He Jianfeng Gao Weizhu Chen T. Zhao 52 9 0 11 Apr 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 365 11,700 0 09 Mar 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,112 0 04 Nov 2016