Daniil Tiapkin

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Alexey NaumovProfessor, HSE UniversityVerified email at hse.ru
Eric MoulinesProfesseur, Ecole Polytechnique, Membre de l'Académie des SciencesVerified email at polytechnique.edu
Michal ValkoChief Models Officer @ Stealth Startup, Inria & MVA - Ex: Llama at Meta; Gemini and BYOL @ DeepmindVerified email at meta.com
Prof. Dr. Denis BelomestnyDuisburg-Essen UniversityVerified email at uni-due.de
Pierre MénardOvGU MagdeburgVerified email at inria.fr
Sergey SamsonovHSE university, MoscowVerified email at hse.ru
Daniele CalandrielloResearch Scientist, DeepMindVerified email at google.com
Nikita MorozovHSE UniversityVerified email at hse.ru
Rémi MunosFAIR, MetaVerified email at inria.fr
Yunhao TangResearch Scientist, Llama research team; Previously, DeepMindVerified email at columbia.edu
Dmitry VetrovProfessor of Computer Science at Constructor University, BremenVerified email at constructor.university
Alexander GasnikovMIPTVerified email at mipt.ru
Sholom SchechtmanTélécom SudParisVerified email at telecom-sudparis.eu
Michael MuehlebachMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Darina DvinskikhHSE UniversityVerified email at hse.ru
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
Generative Flow Networks as Entropy-Regularized RL D Tiapkin, N Morozov, A Naumov, D Vetrov AISTATS-2024, 2023	23	2023
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	19	2022
Fast Rates for Maximum Entropy Exploration D Tiapkin, D Belomestny, D Calandriello, E Moulines, R Munos, ... International Conference on Machine Learning, 2023	17	2023
Stochastic saddle-point optimization for the Wasserstein barycenter problem D Tiapkin, A Gasnikov, P Dvurechensky Optimization Letters 16 (7), 2145-2175, 2022	12	2022
Primal-Dual Stochastic Mirror Descent for MDPs D Tiapkin, A Gasnikov International Conference on Artificial Intelligence and Statistics, 9723-9740, 2022	12	2022
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	11	2022
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	9*	2024
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	9	2023
Demonstration-Regularized RL D Tiapkin, D Belomestny, D Calandriello, E Moulines, A Naumov, ... ICLR-2024, 2023	8*	2023
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	6	2024
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	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
Improving GFlowNets with Monte Carlo Tree Search N Morozov, D Tiapkin, S Samsonov, A Naumov, D Vetrov arXiv preprint arXiv:2406.13655, 2024	2	2024
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents S Labbi, D Tiapkin, L Mancini, P Mangold, E Moulines arXiv preprint arXiv:2410.22908, 2024	1	2024
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization T Gritsaev, N Morozov, S Samsonov, D Tiapkin arXiv preprint arXiv:2410.15474, 2024	1	2024
Revisiting Non-Acyclic GFlowNets in Discrete Environments N Morozov, I Maksimov, D Tiapkin, S Samsonov arXiv preprint arXiv:2502.07735, 2025		2025
On Teacher Hacking in Language Model Distillation D Tiapkin, D Calandriello, J Ferret, S Perrin, N Vieillard, A Ramé, ... arXiv preprint arXiv:2502.02671, 2025		2025
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

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