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Sergey Samsonov
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2020 – today
- 2024
- [j7]Nikita Puchkin, Sergey Samsonov, Denis Belomestny, Eric Moulines, Alexey Naumov:
Rates of convergence for density estimation with generative adversarial networks. J. Mach. Learn. Res. 25: 29:1-29:47 (2024) - [j6]Denis Belomestny, Artur Goldman, Alexey Naumov, Sergey Samsonov
:
Theoretical guarantees for neural control variates in MCMC. Math. Comput. Simul. 220: 382-405 (2024) - [c11]Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines:
Queuing dynamics of asynchronous Federated Learning. AISTATS 2024: 1711-1719 - [c10]Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines:
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability. COLT 2024: 4511-4547 - [i18]Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines:
SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning. CoRR abs/2402.04114 (2024) - [i17]Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines:
Queuing dynamics of asynchronous Federated Learning. CoRR abs/2405.00017 (2024) - [i16]Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov:
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning. CoRR abs/2405.16644 (2024) - [i15]Nikita Morozov, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry Vetrov:
Improving GFlowNets with Monte Carlo Tree Search. CoRR abs/2406.13655 (2024) - [i14]Marina Sheshukova, Denis Belomestny, Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation. CoRR abs/2410.05106 (2024) - [i13]Timofei Gritsaev, Nikita Morozov, Sergey Samsonov, Daniil Tiapkin:
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization. CoRR abs/2410.15474 (2024) - 2023
- [j5]Denis Belomestny
Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations. Neural Networks 161: 242-253 (2023) - [c9]Sergey Samsonov:
Seasonal spatial-temporal variability in radar penetration depth. CENTERIS/ProjMAN/HCist 2023: 1387-1392 - [c8]Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines:
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. NeurIPS 2023 - [i12]Denis Belomestny, Artur Goldman, Alexey Naumov, Sergey Samsonov:
Theoretical guarantees for neural control variates in MCMC. CoRR abs/2304.01111 (2023) - [i11]Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines:
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. CoRR abs/2305.15938 (2023) - [i10]Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines:
Finite-Sample Analysis of the Temporal Difference Learning. CoRR abs/2310.14286 (2023) - 2022
- [j4]Denis Belomestny, Eric Moulines, Sergey Samsonov
Variance reduction for additive functionals of Markov chains via martingale representations. Stat. Comput. 32(1): 16 (2022) - [c7]Daniil Tiapkin
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses. ICML 2022: 21380-21431 - [c6]Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson:
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. NeurIPS 2022 - [c5]Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines:
Local-Global MCMC kernels: the best of both worlds. NeurIPS 2022 - [i9]Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Ménard:
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses. CoRR abs/2205.07704 (2022) - [i8]Denis Belomestny, Alexey Naumov, Nikita Puchkin, Sergey Samsonov:
Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations. CoRR abs/2206.09527 (2022) - [i7]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation. CoRR abs/2207.04475 (2022) - [i6]Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson:
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. CoRR abs/2207.06364 (2022) - 2021
- [j3]Denis Belomestny
Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC. SIAM/ASA J. Uncertain. Quantification 9(2): 507-535 (2021) - [c4]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai:
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. COLT 2021: 1711-1752 - [c3]Nicolas d'Oreye
MasTer: A Full Automatic Multi-Satellite InSAR Mass Processing Tool for Rapid Incremental 2D Ground Deformation Time Series. IGARSS 2021: 1899-1902 - [c2]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai:
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. NeurIPS 2021: 30063-30074 - [i5]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai:
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. CoRR abs/2102.00185 (2021) - [i4]Denis Belomestny, Ilya Levin, Eric Moulines, Alexey Naumov, Sergey Samsonov, Veronika Zorina:
Model-free policy evaluation in Reinforcement Learning via upper solutions. CoRR abs/2105.02135 (2021) - [i3]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai:
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. CoRR abs/2106.01257 (2021) - [i2]Evgeny Lagutin, Daniil Selikhanovych, Achille Thin, Sergey Samsonov, Alexey Naumov, Denis Belomestny, Maxim Panov, Eric Moulines:
Ex2MCMC: Sampling through Exploration Exploitation. CoRR abs/2111.02702 (2021) - 2020
- [j2]Denis Belomestny, Leonid Iosipoi
Variance reduction for Markov chains with application to MCMC. Stat. Comput. 30(4): 973-997 (2020)
2010 – 2019
- 2019
- [i1]Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Variance reduction for Markov chains with application to MCMC. CoRR abs/1910.03643 (2019) - 2017
- [c1]Sadra Karimzadeh
Block-based damage assessment of the 2012 Ahar-Varzaghan, Iran, earthquake through SAR remote senisng data. IGARSS 2017: 1546-1549
2000 – 2009
- 2007
- [j1]Evgeny Zatulovskiy
Docking study on mammalian CTR1 copper importer motifs. BMC Syst. Biol. 1(S-1): P54 (2007)
Coauthor Index
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last updated on 2024-12-10 20:48 CET by the dblp team
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