895 citations · 5.3k across the 104 of their papers we have counts for
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math.OC2016★ 4 cited
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
Xingguo Li, Tuo Zhao, Raman Arora +2
The cyclic block coordinate descent-type (CBCD-type) methods, which performs iterative updates for a few coordinates (a block) simultaneously throughout the procedure, have shown r…
math.OC2016★ 34 cited
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization
Davood Hajinezhad, Mingyi Hong, Tuo Zhao +1
We study a stochastic and distributed algorithm for nonconvex problems whose objective consists of a sum of nonconvex -smooth functions, plus a nonsmooth regularizer. Th…
math.OC2016★ 31 cited
Decomposing Linearly Constrained Nonconvex Problems by a Proximal Primal Dual Approach: Algorithms, Convergence, and Applications
Mingyi Hong
In this paper, we propose a new decomposition approach named the proximal primal dual algorithm (Prox-PDA) for smooth nonconvex linearly constrained optimization problems. The prop…