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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…
math.OC2019★ 1 cited
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
Feihu Huang, Bin Gu, Zhouyuan Huo +2
Proximal gradient method has been playing an important role to solve many machine learning tasks, especially for the nonsmooth problems. However, in some machine learning problems…