Convergence and concentration properties of constant step-size SGD through Markov chains

20 June 2023

Papers citing "Convergence and concentration properties of constant step-size SGD through Markov chains"

9 / 9 papers shown

Title
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression Yixuan Zhang Dongyan Yudong Chen Qiaomin Xie 24 0 0 11 Apr 2025
Online Inference for Quantiles by Constant Learning-Rate Stochastic Gradient Descent Ziyang Wei Jiaqi Li Likai Chen W. Wu 48 0 0 04 Mar 2025
Coupling-based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent Xiang Li Qiaomin Xie 76 0 0 15 Dec 2024
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation Marina Sheshukova Denis Belomestny Alain Durmus Eric Moulines Alexey Naumov S. Samsonov 33 1 0 07 Oct 2024
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning Nikhil Ghosh Spencer Frei Wooseok Ha Ting Yu MLT 32 3 0 06 Aug 2023
A High Probability Analysis of Adaptive SGD with Momentum Xiaoyun Li Francesco Orabona 87 65 0 28 Jul 2020
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 133 1,198 0 16 Aug 2016
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 121 259 0 10 Dec 2012
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 99 570 0 08 Dec 2012