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Nash Equilibria and Pitfalls of Adversarial Training in Adversarial
  Robustness Games

Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games

23 October 2022
Maria-Florina Balcan
Rattana Pukdee
Pradeep Ravikumar
Hongyang R. Zhang
    AAML
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Papers citing "Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games"

2 / 2 papers shown
Title
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from
  a Minimax Game Perspective
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
Yifei Wang
Liangchen Li
Jiansheng Yang
Zhouchen Lin
Yisen Wang
16
11
0
30 Oct 2023
Game Theoretic Mixed Experts for Combinational Adversarial Machine
  Learning
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning
Ethan Rathbun
Kaleel Mahmood
Sohaib Ahmad
Caiwen Ding
Marten van Dijk
AAML
8
4
0
26 Nov 2022
1