110 citations · 112 across the 5 of their papers we have counts for
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math.OC2020
Adaptive Primal-Dual Stochastic Gradient Method for Expectation-constrained Convex Stochastic Programs
Yonggui Yan, Yangyang Xu
Stochastic gradient methods (SGMs) have been widely used for solving stochastic optimization problems. A majority of existing works assume no constraints or easy-to-project constra…
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…