Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent
Probability
2023-02-15 v1 Machine Learning
Analysis of PDEs
Machine Learning
Abstract
We propose new limiting dynamics for stochastic gradient descent in the small learning rate regime called stochastic modified flows. These SDEs are driven by a cylindrical Brownian motion and improve the so-called stochastic modified equations by having regular diffusion coefficients and by matching the multi-point statistics. As a second contribution, we introduce distribution dependent stochastic modified flows which we prove to describe the fluctuating limiting dynamics of stochastic gradient descent in the small learning rate - infinite width scaling regime.
Cite
@article{arxiv.2302.07125,
title = {Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent},
author = {Benjamin Gess and Sebastian Kassing and Vitalii Konarovskyi},
journal= {arXiv preprint arXiv:2302.07125},
year = {2023}
}
Comments
24 pages