Paper ID: 2410.08449 • Published Oct 11, 2024

Finite Sample and Large Deviations Analysis of Stochastic Gradient Algorithm with Correlated Noise

George Yin, Vikram Krishnamurthy
TL;DR
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We analyze the finite sample regret of a decreasing step size stochastic gradient algorithm. We assume correlated noise and use a perturbed Lyapunov function as a systematic approach for the analysis. Finally we analyze the escape time of the iterates using large deviations theory.