2 citations · 7 across the 14 of their papers we have counts for
3 papers · 1 filter
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
Quoc Tran-Dinh, Trang H. Tran, Lam M. Nguyen
This paper aims at developing novel shuffling gradient-based methods for tackling two classes of minimax problems: nonconvex-linear and nonconvex-strongly concave settings. The fir…
Shuffling Momentum Gradient Algorithm for Convex Optimization
Trang H. Tran, Quoc Tran-Dinh, Lam M. Nguyen
The Stochastic Gradient Descent method (SGD) and its stochastic variants have become methods of choice for solving finite-sum optimization problems arising from machine learning an…
Stochastic ISTA/FISTA Adaptive Step Search Algorithms for Convex Composite Optimization
Lam M. Nguyen, Katya Scheinberg, Trang H. Tran
We develop and analyze stochastic variants of ISTA and a full backtracking FISTA algorithms [Beck and Teboulle, 2009, Scheinberg et al., 2014] for composite optimization without th…