Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning

22 February 2023

Papers citing "Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning"

8 / 8 papers shown

Title
Demystifying the Myths and Legends of Nonconvex Convergence of SGD Aritra Dutta El Houcine Bergou Soumia Boucherouite Nicklas Werge M. Kandemir Xin Li 18 0 0 19 Oct 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization G. Fort Eric Moulines 33 6 0 02 Jan 2023
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 19 3 0 09 Nov 2022
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks Huu Le R. Høier Che-Tsung Lin Christopher Zach 40 15 0 06 Dec 2021
Linearly Converging Error Compensated SGD Eduard A. Gorbunov D. Kovalev Dmitry Makarenko Peter Richtárik 163 77 0 23 Oct 2020
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights Weijie Su Stephen P. Boyd Emmanuel J. Candes 97 1,150 0 04 Mar 2015
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 99 571 0 08 Dec 2012
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 164 683 0 07 Dec 2010