29 citations · 40 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 11 cited
Stronger and Faster Wasserstein Adversarial Attacks
Kaiwen Wu, Allen Houze Wang, Yaoliang Yu
Deep models, while being extremely flexible and accurate, are surprisingly vulnerable to "small, imperceptible" perturbations known as adversarial attacks. While the majority of ex…
cs.LG2019
Understanding Adversarial Robustness: The Trade-off between Minimum and Average Margin
Kaiwen Wu, Yaoliang Yu
Deep models, while being extremely versatile and accurate, are vulnerable to adversarial attacks: slight perturbations that are imperceptible to humans can completely flip the pred…
cs.LG2019★ 29 cited
Distributional Reinforcement Learning for Efficient Exploration
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao +3
In distributional reinforcement learning (RL), the estimated distribution of value function models both the parametric and intrinsic uncertainties. We propose a novel and efficient…