49 citations · 408 across the 42 of their papers we have counts for
6 papers · 1 filter
Exploiting Token and Path-based Representations of Code for Identifying Security-Relevant Commits
Achyudh Ram, Ji Xin, Meiyappan Nagappan +4
Public vulnerability databases such as CVE and NVD account for only 60% of security vulnerabilities present in open-source projects, and are known to suffer from inconsistent quali…
Convergence of Gradient Methods on Bilinear Zero-Sum Games
Guojun Zhang, Yaoliang Yu
Min-max formulations have attracted great attention in the ML community due to the rise of deep generative models and adversarial methods, while understanding the dynamics of gradi…
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…
Tails of Lipschitz Triangular Flows
Priyank Jaini, Ivan Kobyzev, Yaoliang Yu +1
We investigate the ability of popular flow based methods to capture tail-properties of a target density by studying the increasing triangular maps used in these flow methods acting…
Sum-of-Squares Polynomial Flow
Priyank Jaini, Kira A. Selby, Yaoliang Yu
Triangular map is a recent construct in probability theory that allows one to transform any source probability density function to any target density function. Based on triangular…
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…