146 citations · 194 across the 10 of their papers we have counts for
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math.OC2019★ 146 cited
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization
Hao Yu, Rong Jin, Sen Yang
Recent developments on large-scale distributed machine learning applications, e.g., deep neural networks, benefit enormously from the advances in distributed non-convex optimizatio…
math.OC2019★ 1 cited
Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses
Rong Jin, David Simchi-Levi, Li Wang +2
The recent rising popularity of ultra-fast delivery services on retail platforms fuels the increasing use of urban warehouses, whose proximity to customers makes fast deliveries vi…
math.OC2019★ 2 cited
On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Optimization
Yi Xu, Zhuoning Yuan, Sen Yang +2
Extrapolation is a well-known technique for solving convex optimization and variational inequalities and recently attracts some attention for non-convex optimization. Several recen…