34 citations · 42 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 8 cited
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds
Yingxue Zhou, Xiangyi Chen, Mingyi Hong +2
We study differentially private (DP) algorithms for stochastic non-convex optimization. In this problem, the goal is to minimize the population loss over a -dimensional space gi…
cs.LG2019★ 34 cited
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
Xiangyi Chen, Sijia Liu, Kaidi Xu +4
The adaptive momentum method (AdaMM), which uses past gradients to update descent directions and learning rates simultaneously, has become one of the most popular first-order optim…
cs.LG2019
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML
Sijia Liu, Songtao Lu, Xiangyi Chen +5
In this paper, we study the problem of constrained robust (min-max) optimization ina black-box setting, where the desired optimizer cannot access the gradients of the objective fun…