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Sergey Samsonov
Sergey Samsonov
HSE university, Moscow
Verified email at hse.ru - Homepage
Title
Cited by
Cited by
Year
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
A Durmus, E Moulines, A Naumov, S Samsonov, K Scaman, HT Wai
Advances in Neural Information Processing Systems 34, 30063-30074, 2021
452021
Finite-time high-probability bounds for Polyak–Ruppert averaged iterates of linear stochastic approximation
A Durmus, E Moulines, A Naumov, S Samsonov
Mathematics of Operations Research 50 (2), 935-964, 2025
432025
Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations
D Belomestny, A Naumov, N Puchkin, S Samsonov
Neural Networks 161, 242-253, 2023
432023
On the stability of random matrix product with markovian noise: Application to linear stochastic approximation and td learning
A Durmus, E Moulines, A Naumov, S Samsonov, HT Wai
Conference on Learning Theory, 1711-1752, 2021
342021
Rates of convergence for density estimation with generative adversarial networks
N Puchkin, S Samsonov, D Belomestny, E Moulines, A Naumov
Journal of Machine Learning Research 25 (29), 1-47, 2024
31*2024
Local-Global MCMC kernels: the best of both worlds
S Samsonov, E Lagutin, M Gabrié, A Durmus, A Naumov, E Moulines
Advances in Neural Information Processing Systems 35, 5178-5193, 2022
302022
First order methods with markovian noise: from acceleration to variational inequalities
A Beznosikov, S Samsonov, M Sheshukova, A Gasnikov, A Naumov, ...
Advances in Neural Information Processing Systems 36, 44820-44835, 2023
282023
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
D Tiapkin, D Belomestny, É Moulines, A Naumov, S Samsonov, Y Tang, ...
International Conference on Machine Learning, 21380-21431, 2022
282022
Variance reduction for Markov chains with application to MCMC
D Belomestny, L Iosipoi, E Moulines, A Naumov, S Samsonov
Statistics and Computing 30 (4), 973-997, 2020
282020
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability
S Samsonov, D Tiapkin, A Naumov, E Moulines
The Thirty Seventh Annual Conference on Learning Theory, 4511-4547, 2024
20*2024
Gaussian approximation and multiplier bootstrap for polyak-ruppert averaged linear stochastic approximation with applications to td learning
S Samsonov, E Moulines, QM Shao, ZS Zhang, A Naumov
Advances in Neural Information Processing Systems 37, 12408-12460, 2025
172025
Br-snis: bias reduced self-normalized importance sampling
G Cardoso, S Samsonov, A Thin, E Moulines, J Olsson
Advances in Neural Information Processing Systems 35, 716-729, 2022
152022
Variance reduction for dependent sequences with applications to stochastic gradient MCMC
D Belomestny, L Iosipoi, E Moulines, A Naumov, S Samsonov
SIAM/ASA Journal on Uncertainty Quantification 9 (2), 507-535, 2021
132021
Queuing dynamics of asynchronous Federated Learning
L Leconte, M Jonckheere, S Samsonov, E Moulines
International Conference on Artificial Intelligence and Statistics, 1711-1719, 2024
112024
Rosenthal-type inequalities for linear statistics of Markov chains
A Durmus, E Moulines, A Naumov, S Samsonov, M Sheshukova
arXiv preprint arXiv:2303.05838, 2023
112023
Theoretical guarantees for neural control variates in MCMC
D Belomestny, A Goldman, A Naumov, S Samsonov
Mathematics and Computers in Simulation 220, 382-405, 2024
102024
Scafflsa: Taming heterogeneity in federated linear stochastic approximation and td learning
P Mangold, S Samsonov, S Labbi, I Levin, R Alami, A Naumov, ...
The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
102024
Probability and moment inequalities for additive functionals of geometrically ergodic Markov chains
A Durmus, E Moulines, A Naumov, S Samsonov
Journal of Theoretical Probability 37 (3), 2184-2233, 2024
92024
Variance reduction for additive functionals of Markov chains via martingale representations
D Belomestny, E Moulines, S Samsonov
Statistics and Computing 32 (1), 1-22, 2022
82022
Statistical inference for Linear Stochastic Approximation with Markovian Noise
S Samsonov, M Sheshukova, E Moulines, A Naumov
arXiv preprint arXiv:2505.19102, 2025
72025
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Articles 1–20