2025
A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging
NeurIPS 2025poster
Polyak–Ruppert averaging is a widely used technique to achieve the optimal asymptotic variance of stochastic approximation (SA) algorithms, yet its high-probability performance guarantees remain underexplored in general settings. In this paper, we present a general framework for establishing non-asy…