Samsonov, Sergey

17 publications

ICLR 2025 Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov

ICLR 2025 Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization Timofei Gritsaev, Nikita Morozov, Sergey Samsonov, Daniil Tiapkin

AISTATS 2025 Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines

ICML 2025 Revisiting Non-Acyclic GFlowNets in Discrete Environments Nikita Morozov, Ian Maksimov, Daniil Tiapkin, Sergey Samsonov

NeurIPS 2025 Statistical Inference for Linear Stochastic Approximation with Markovian Noise Sergey Samsonov, Marina Sheshukova, Eric Moulines, Alexey Naumov

NeurIPS 2024 Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov

COLT 2024 Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines

ICMLW 2024 Improving GFlowNets with Monte Carlo Tree Search Nikita Morozov, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry Vetrov

AISTATS 2024 Queuing Dynamics of Asynchronous Federated Learning Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines

JMLR 2024 Rates of Convergence for Density Estimation with Generative Adversarial Networks Nikita Puchkin, Sergey Samsonov, Denis Belomestny, Eric Moulines, Alexey Naumov

NeurIPS 2024 SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Reda Alami, Alexey Naumov, Eric Moulines

NeurIPS 2023 First Order Methods with Markovian Noise: From Acceleration to Variational Inequalities Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander Gasnikov, Alexey Naumov, Eric Moulines

NeurIPS 2022 BR-SNIS: Bias Reduced Self-Normalized Importance Sampling Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson

ICML 2022 From Dirichlet to Rubin: Optimistic Exploration in RL Without Bonuses Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Menard

NeurIPS 2022 Local-Global MCMC Kernels: The Best of Both Worlds Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines

COLT 2021 On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai

NeurIPS 2021 Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai