22 citations · 109 across the 34 of their papers we have counts for
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math.OC2018★ 5 cited
Analyzing and provably improving fixed budget ranking and selection algorithms
Di Wu, Enlu Zhou
This paper studies the fixed budget formulation of the Ranking and Selection (R&S) problem with independent normal samples, where the goal is to investigate different algorithms' c…
cs.LG2018
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization
Tianyi Liu, Shiyang Li, Jianping Shi +2
Asynchronous momentum stochastic gradient descent algorithms (Async-MSGD) is one of the most popular algorithms in distributed machine learning. However, its convergence properties…
cs.LG2018★ 4 cited
A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization
Tianyi Liu, Zhehui Chen, Enlu Zhou +1
Momentum Stochastic Gradient Descent (MSGD) algorithm has been widely applied to many nonconvex optimization problems in machine learning, e.g., training deep neural networks, vari…