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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.

P. Mangold, S. Samsonov, S. Labbi, I. Levin, R. Alami, A. Naumov, and E. Moulines. CoRR, (2024)

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Sergey Samsonov

Sergey Libert

Sergey Gorbunov

Sergey Stepanov

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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.P. Mangold, S. Samsonov, S. Labbi, I. Levin, R. Alami, A. Naumov, and E. Moulines. CoRR, (2024)Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations.D. Belomestny, A. Naumov, N. Puchkin, and S. Samsonov. CoRR, (2022)First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities.A. Beznosikov, S. Samsonov, M. Sheshukova, A. Gasnikov, A. Naumov, and E. Moulines. CoRR, (2023)Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation.A. Durmus, E. Moulines, A. Naumov, and S. Samsonov. CoRR, (2022)Theoretical guarantees for neural control variates in MCMC.D. Belomestny, A. Goldman, A. Naumov, and S. Samsonov. CoRR, (2023)Variance reduction for Markov chains with application to MCMC.D. Belomestny, L. Iosipoi, E. Moulines, A. Naumov, and S. Samsonov. Stat. Comput., 30 (4): 973-997 (2020)MasTer: A Full Automatic Multi-Satellite InSAR Mass Processing Tool for Rapid Incremental 2D Ground Deformation Time Series.N. d'Oreye, D. Derauw, S. Samsonov, M. Jaspard, and D. Smittarello. IGARSS, page 1899-1902. IEEE, (2021)Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize.A. Durmus, E. Moulines, A. Naumov, S. Samsonov, K. Scaman, and H. Wai. NeurIPS, page 30063-30074. (2021)Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC.D. Belomestny, L. Iosipoi, E. Moulines, A. Naumov, and S. Samsonov. SIAM/ASA J. Uncertain. Quantification, 9 (2): 507-535 (2021)Ex2MCMC: Sampling through Exploration Exploitation.E. Lagutin, D. Selikhanovych, A. Thin, S. Samsonov, A. Naumov, D. Belomestny, M. Panov, and E. Moulines. CoRR, (2021)

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Disambiguation of "Samsonov, Sergey"

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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.

Please choose a person to relate this publication to

Sergey Samsonov

Sergey Samsonov

Sergey Libert

Sergey Gorbunov

Sergey Stepanov

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Samsonov, Sergey"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.

Please choose a person to relate this publication to

Sergey Samsonov

Sergey Samsonov

Sergey Libert

Sergey Gorbunov

Sergey Stepanov

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
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Chicago
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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.