Towards closing the gap between the theory and practice of SVRG

31 July 2019

Papers citing "Towards closing the gap between the theory and practice of SVRG"

8 / 8 papers shown

Title
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations Yao Shu Jiongfeng Fang Y. He Fei Richard Yu 35 0 0 18 Feb 2024
Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions S. Choudhury Eduard A. Gorbunov Nicolas Loizou 27 13 0 27 Feb 2023
SVRG Meets AdaGrad: Painless Variance Reduction Benjamin Dubois-Taine Sharan Vaswani Reza Babanezhad Mark Schmidt Simon Lacoste-Julien 20 18 0 18 Feb 2021
Variance-Reduced Methods for Machine Learning Robert Mansel Gower Mark Schmidt Francis R. Bach Peter Richtárik 21 111 0 02 Oct 2020
Stochastic Hamiltonian Gradient Methods for Smooth Games Nicolas Loizou Hugo Berard Alexia Jolicoeur-Martineau Pascal Vincent Simon Lacoste-Julien Ioannis Mitliagkas 39 50 0 08 Jul 2020
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation Robert Mansel Gower Othmane Sebbouh Nicolas Loizou 25 74 0 18 Jun 2020
Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball Othmane Sebbouh Robert Mansel Gower Aaron Defazio 19 22 0 14 Jun 2020
Sampling and Update Frequencies in Proximal Variance-Reduced Stochastic Gradient Methods Martin Morin Pontus Giselsson 27 4 0 13 Feb 2020