58 citations · 305 across the 33 of their papers we have counts for
5 papers · 1 filter
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities
Chaobing Song, Zhengyuan Zhou, Yichao Zhou +2
The optimization problems associated with training generative adversarial neural networks can be largely reduced to certain {\em non-monotone} variational inequality problems (VIPs…
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization
Chaobing Song, Yong Jiang, Yi Ma
In this paper, we introduce a simplified and unified method for finite-sum convex optimization, named \emph{Variance Reduction via Accelerated Dual Averaging (VRADA)}. In both gene…
Breaking the Optimal Rate for a Class of Minimax Problems
Chaobing Song, Yong Jiang, Yi Ma
It is known that for convex optimization , the best possible rate of first order accelerated methods is . However, for th…
Inexact Proximal Cubic Regularized Newton Methods for Convex Optimization
Chaobing Song, Ji Liu, Yong Jiang
In this paper, we use Proximal Cubic regularized Newton Methods (PCNM) to optimize the sum of a smooth convex function and a non-smooth convex function, where we use inexact gradie…
Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex
Chaobing Song, Shaobo Cui, Yong Jiang +1
In this paper we study the well-known greedy coordinate descent (GCD) algorithm to solve -regularized problems and improve GCD by the two popular strategies: Nesterov's acc…