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Vladimir Solodkin

2 accepted papers

2026

Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry

AAAI 2026technical

This paper examines a variety of classical optimization problems, including well-known minimization tasks and more general variational inequalities. We consider a stochastic formulation of these problems and, unlike most previous work, we take into account the complex Markov nature of the noise. We

Cited by 0SourcePDFScholar
2024

Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases

AISTATS 2024poster

The Conditional Gradient (or Frank-Wolfe) method is one of the most well-known methods for solving constrained optimization problems appearing in various machine learning tasks. The simplicity of iteration and applicability to many practical problems helped the method to gain popularity in the commu…

Cited by 4SourcePDFScholar