23 citations · 39 across the 12 of their papers we have counts for
Showing math.OCShow all
3 papers · 1 filter
math.OC2020★ 23 cited
Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization
Feihu Huang, Shangqian Gao, Jian Pei +1
In the paper, we propose a class of accelerated zeroth-order and first-order momentum methods for both nonconvex mini-optimization and minimax-optimization. Specifically, we propos…
math.OC2019★ 5 cited
Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity
Feihu Huang, Shangqian Gao, Jian Pei +1
Zeroth-order (a.k.a, derivative-free) methods are a class of effective optimization methods for solving complex machine learning problems, where gradients of the objective function…
math.OC2019
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization
Feihu Huang, Shangqian Gao, Songcan Chen +1
Alternating direction method of multipliers (ADMM) is a popular optimization tool for the composite and constrained problems in machine learning. However, in many machine learning…