6 citations · 13 across the 4 of their papers we have counts for
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math.OC2020★ 6 cited
Momentum-based variance-reduced proximal stochastic gradient method for composite nonconvex stochastic optimization
Yangyang Xu, Yibo Xu
Stochastic gradient methods (SGMs) have been extensively used for solving stochastic problems or large-scale machine learning problems. Recent works employ various techniques to im…
math.OC2020★ 2 cited
Parallel and distributed asynchronous adaptive stochastic gradient methods
Yangyang Xu, Yibo Xu, Yonggui Yan +3
Stochastic gradient methods (SGMs) are the predominant approaches to train deep learning models. The adaptive versions (e.g., Adam and AMSGrad) have been extensively used in practi…