Author

Alexey Naumov

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#machine learning Conference Aug 2025

High-Order Error Bounds for Markovian LSA with Richardson-Romberg Extrapolation

In this paper, we study the bias and high-order error bounds of the Linear Stochastic Approximation (LSA) algorithm with Polyak-Ruppert (PR) averaging under Markovian noise. We focus on the version of the algorithm with constant step size and propose a novel decomposition of the bias via a linearization technique. We a...

I. Levin, Alexey Naumov, Sergey Samsonov · AAAI Conference on Artificia... · 2 citations

#machine learning Dec 2025

Statistical analysis of Inverse Entropy-regularized Reinforcement Learning

A statistical framework for Inverse Entropy-regularized Reinforcement Learning is developed that resolves ambiguity by combining entropy regularization with a least-squares reconstruction of the reward from the soft Bellman residual, leading to a unique and well-defined so-called least-squares reward consistent with th...

D. Belomestny, Alexey Naumov, Sergey Samsonov · arXiv.org · 0 citations