Dinghuai Zhang

PAC Learnability of Approximate Nash Equilibrium in Bimatrix Games

2021 · arXiv (Cornell University)

Computing Nash equilibrium in bimatrix games is PPAD-hard, and many works have focused on the approximate solutions. When games are generated from a fixed unknown distribution, learning a Nash predictor via data-driven approaches can be …

Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets

2023 · arXiv (Cornell University)

Despite incredible advances, deep learning has been shown to be susceptible to adversarial attacks. Numerous approaches have been proposed to train robust networks both empirically and certifiably. However, most of them defend against only a …