UAI 2023poster4 citations
Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis.
Swetha Ganesh, Rohan Deb, Gugan Thoppe, Amarjit Budhiraja
Abstract
Stochastic Heavy Ball (SHB) and Nesterov’s Accelerated Stochastic Gradient (ASG) are popular momentum methods in optimization. While the benefits of these acceleration ideas in deterministic settings are well understood, their advantages in stochastic optimization are unclear. Several works have recently claimed that SHB and ASG always help in stochastic optimization. Our work shows that i.) these claims are either flawed or one-sided (e.g., consider only the bias term but not the variance), and ii.) when both these terms are accounted for, SHB and ASG do not always help. Specifically, for
BibTeX
@InProceedings{pmlr-v216-ganesh23a,
title = {Does Momentum Help in Stochastic Optimization? {A} Sample Complexity Analysis.},
author = {Ganesh, Swetha and Deb, Rohan and Thoppe, Gugan and Budhiraja, Amarjit},
booktitle = {Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence},
pages = {602--612},
year = {2023},
editor = {Evans, Robin J. and Shpitser, Ilya},
volume = {216},
series = {Proceedings of Machine Learning Research},
month = {31 Jul--04 Aug},
publisher = {PMLR},
pdf = {https://proceedings.mlr.press/v216/ganesh23a/ganesh23a.pdf},
url = {https://proceedings.mlr.press/v216/ganesh23a.html},
abstract = {Stochastic Heavy Ball (SHB) and Nesterov’s Accelerated Stochastic Gradient (ASG) are popular momentum methods in optimization. While the benefits of these acceleration ideas in deterministic settings are well understood, their advantages in stochastic optimization are unclear. Several works have recently claimed that SHB and ASG always help in stochastic optimization. Our work shows that i.) these claims are either flawed or one-sided (e.g., consider only the bias term but not the variance), and ii.) when both these terms are accounted for, SHB and ASG do not always help. Specifically, for