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Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent

14 February 2023
Benjamin Gess
Sebastian Kassing
Vitalii Konarovskyi
    DiffM
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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.

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