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Bibliographic Details
Main Authors:	Avetisyan, Arutyun, Dvinskikh, Darina, Gasnikov, Alexander, Temlyakov, Vladimir, Tupitsa, Nazarii, Turdakov, Denis
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control
Online Access:	https://arxiv.org/abs/2605.16875
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Table of Contents:

This paper aims to motivate stochastic optimization problems from a statistical perspective and a statistical learning perspective, where the goal is to maximize the log-likelihood or minimize the population risk. We briefly describe the two main approaches: offline (Monte Carlo / Sample Average Approximation) and online (Stochastic Approximation) approaches -- to solve the expectation minimization problems.