Tiapkin, Daniil

18 publications

AISTATS 2025 Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines

ICML 2025 Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini, Mathieu Lauriere, Eric Moulines

AISTATS 2025 Narrowing the Gap Between Adversarial and Stochastic MDPs via Policy Optimization Daniil Tiapkin, Evgenii Chzhen, Gilles Stoltz

ICML 2025 On Teacher Hacking in Language Model Distillation Daniil Tiapkin, Daniele Calandriello, Johan Ferret, Sarah Perrin, Nino Vieillard, Alexandre Rame, Mathieu Blondel

ICLR 2025 Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization Timofei Gritsaev, Nikita Morozov, Sergey Samsonov, Daniil Tiapkin

ICML 2025 Revisiting Non-Acyclic GFlowNets in Discrete Environments Nikita Morozov, Ian Maksimov, Daniil Tiapkin, Sergey Samsonov

ICLR 2024 Demonstration-Regularized RL Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Menard

AISTATS 2024 Generative Flow Networks as Entropy-Regularized RL Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry P Vetrov

COLT 2024 Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines

ICMLW 2024 Improving GFlowNets with Monte Carlo Tree Search Nikita Morozov, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry Vetrov

ICML 2024 Incentivized Learning in Principal-Agent Bandit Games Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, Eric Moulines, Michael Jordan, El-Mahdi El-Mhamdi, Alain Oliviero Durmus

ICML 2023 Fast Rates for Maximum Entropy Exploration Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Remi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Menard

NeurIPS 2023 Model-Free Posterior Sampling via Learning Rate Randomization Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Remi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard

COLT 2023 Orthogonal Directions Constrained Gradient Method: From Non-Linear Equality Constraints to Stiefel Manifold Sholom Schechtman, Daniil Tiapkin, Michael Muehlebach, Éric Moulines

AISTATS 2022 Primal-Dual Stochastic Mirror Descent for MDPs Daniil Tiapkin, Alexander Gasnikov

ICML 2022 From Dirichlet to Rubin: Optimistic Exploration in RL Without Bonuses Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Menard

NeurIPS 2022 Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Remi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard

AISTATS 2021 Improved Complexity Bounds in Wasserstein Barycenter Problem Darina Dvinskikh, Daniil Tiapkin