62 citations · 315 across the 65 of their papers we have counts for
5 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…
Revisiting Extragradient-Type Methods -- Part 1: Generalizations and Sublinear Convergence Rates
Quoc Tran-Dinh, Nghia Nguyen-Trung
This paper presents a comprehensive analysis of the well-known extragradient (EG) method for solving both equations and inclusions. First, we unify and generalize EG for [non]linea…
Variance-Reduced Fast Krasnoselkii-Mann Methods for Finite-Sum Root-Finding Problems
Quoc Tran-Dinh
We propose a new class of fast Krasnoselkii--Mann methods with variance reduction to solve a finite-sum co-coercive equation . Our algorithm is single-loop and leverages a…
Stochastic Variance-Reduced Forward-Reflected-Backward Splitting Methods for Nonmonotone Generalized Equations
Quoc Tran-Dinh
We develop two novel stochastic variance-reduction methods to approximate solutions of a class of nonmonotone [generalized] equations. Our algorithms leverage a new combination of…
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…