Daniil Tiapkin

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Alexey NaumovNational Research University Higher School of EconomicsVerified email at hse.ru
Eric MoulinesProfesseur, Ecole Polytechnique, Membre de l'Académie des SciencesVerified email at polytechnique.edu
Michal ValkoLlama @ Meta Paris & Inria & MVA - Ex: Gemini and BYOL @ Google DeepMindVerified email at meta.com
Prof. Dr. Denis BelomestnyDuisburg-Essen UniversityVerified email at uni-due.de
Pierre MénardOvGU MagdeburgVerified email at inria.fr
Daniele CalandrielloResearch Scientist, DeepMindVerified email at google.com
Sergey SamsonovHSE university, MoscowVerified email at hse.ru
Rémi MunosGoogle DeepMindVerified email at inria.fr
Yunhao TangResearch Scientist, DeepMindVerified email at columbia.edu
Alexander GasnikovMIPTVerified email at mipt.ru
Darina DvinskikhHSE UniversityVerified email at hse.ru
Nikita MorozovHSE UniversityVerified email at hse.ru
Dmitry VetrovProfessor of Computer Science at Constructor University, BremenVerified email at constructor.university
Sholom SchechtmanTélécom SudParisVerified email at telecom-sudparis.eu
Michael MuehlebachMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Pavel DvurechenskyWeierstrass Institute for Applied Analysis and StochasticsVerified email at wias-berlin.de
Mark RowlandResearch Scientist, Google DeepMindVerified email at google.com
Alain DurmusEcole polytechniqueVerified email at polytechnique.edu
antoine scheidPhD student, Ecole polytechniqueVerified email at polytechnique.edu

Daniil Tiapkin

Other namesDaniil Tyapkin, Daniil Nikolaevich Tyapkin

École Polytechnique

Verified email at polytechnique.edu - Homepage

optimization reinforcement learning


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Improved complexity bounds in wasserstein barycenter problem D Dvinskikh, D Tiapkin International Conference on Artificial Intelligence and Statistics, 1738-1746, 2021	28	2021
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses D Tiapkin, D Belomestny, E Moulines, A Naumov, S Samsonov, Y Tang, ... International Conference on Machine Learning, 21380-21431, 2022	15	2022
Stochastic saddle-point optimization for the Wasserstein barycenter problem D Tiapkin, A Gasnikov, P Dvurechensky Optimization Letters 16 (7), 2145-2175, 2022	12	2022
Generative Flow Networks as Entropy-Regularized RL D Tiapkin, N Morozov, A Naumov, D Vetrov AISTATS-2024, 2023	11	2023
Fast Rates for Maximum Entropy Exploration D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ... International Conference on Machine Learning, 2023	9	2023
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ... Neural Information Processing Systems, 2022	9	2022
Primal-Dual Stochastic Mirror Descent for MDPs D Tiapkin, A Gasnikov International Conference on Artificial Intelligence and Statistics, 9723-9740, 2022	9	2022
Demonstration-Regularized RL D Tiapkin, D Belomestny, D Calandriello, E Moulines, A Naumov, ... ICLR-2024, 2023	7*	2023
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold S Schechtman, D Tiapkin, M Muehlebach, E Moulines The Thirty Sixth Annual Conference on Learning Theory, 1228-1258, 2023	6	2023
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	5*	2024
Incentivized Learning in Principal-Agent Bandit Games A Scheid, D Tiapkin, E Boursier, A Capitaine, EME Mhamdi, É Moulines, ... arXiv preprint arXiv:2403.03811, 2024	3	2024
First-Order Constrained Optimization: Non-smooth Dynamical System Viewpoint S Schechtman, D Tiapkin, E Moulines, MI Jordan, M Muehlebach IFAC-PapersOnLine 55 (16), 236-241, 2022	3	2022
Model-free Posterior Sampling via Learning Rate Randomization D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ... Advances in Neural Information Processing Systems 36, 2024	1	2024
A New Bound on the Cumulant Generating Function of Dirichlet Processes P Perrault, D Belomestny, P Ménard, É Moulines, A Naumov, D Tiapkin, ... arXiv preprint arXiv:2409.18621, 2024		2024
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization D Tiapkin, E Chzhen, G Stoltz arXiv preprint arXiv:2407.05704, 2024		2024
Improving GFlowNets with Monte Carlo Tree Search N Morozov, D Tiapkin, S Samsonov, A Naumov, D Vetrov arXiv preprint arXiv:2406.13655, 2024		2024
On the structure of the set of panchromatic colorings of a random hypergraph DN Tyapkin, DA Shabanov Doklady Mathematics 108 (1), 286-290, 2023		2023
Sharp Deviations Bounds for Dirichlet Weighted Sums with Application to analysis of Bayesian algorithms D Belomestny, P Menard, A Naumov, D Tiapkin, M Valko arXiv preprint arXiv:2304.03056, 2023		2023

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