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Bibliographische Detailangaben
Hauptverfasser: Avetisyan, Arutyun, Dvinskikh, Darina, Gasnikov, Alexander, Temlyakov, Vladimir, Tupitsa, Nazarii, Turdakov, Denis
Format: Preprint
Veröffentlicht: 2026
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2605.16875
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Inhaltsangabe:
  • 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.