10 citations · 17 across the 2 of their papers we have counts for
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math.OC2018
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
Blake Woodworth, Jialei Wang, Adam Smith +2
We suggest a general oracle-based framework that captures different parallel stochastic optimization settings described by a dependency graph, and derive generic lower bounds in te…
math.OC2017★ 7 cited
Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations
Jialei Wang, Tong Zhang
We present novel minibatch stochastic optimization methods for empirical risk minimization problems, the methods efficiently leverage variance reduced first-order and sub-sampled h…
math.OC2017★ 10 cited
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
Jialei Wang, Lin Xiao
We consider empirical risk minimization of linear predictors with convex loss functions. Such problems can be reformulated as convex-concave saddle point problems, and thus are wel…