Daniil Tiapkin

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 22

Top Topics

Temporal Difference

Metropolis Hastings

Maximum Entropy

Top Venues

Publications

Daniil Tiapkin, Evgenii Chzhen, Gilles Stoltz
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization. CoRR (2024)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
Demonstration-Regularized RL. ICLR (2024)
Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry P. Vetrov
Generative Flow Networks as Entropy-Regularized RL. AISTATS (2024)
Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, El Mahdi El Mhamdi, Eric Moulines, Michael I. Jordan, Alain Durmus
Incentivized Learning in Principal-Agent Bandit Games. CoRR (2024)
Nikita Morozov, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry Vetrov
Improving GFlowNets with Monte Carlo Tree Search. CoRR (2024)
Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability. COLT (2024)
Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry P. Vetrov
Generative Flow Networks as Entropy-Regularized RL. CoRR (2023)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
Demonstration-Regularized RL. CoRR (2023)
Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines
Finite-Sample Analysis of the Temporal Difference Learning. CoRR (2023)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard
Fast Rates for Maximum Entropy Exploration. CoRR (2023)
Sholom Schechtman, Daniil Tiapkin, Michael Muehlebach, Éric Moulines
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold. COLT (2023)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
Model-free Posterior Sampling via Learning Rate Randomization. CoRR (2023)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard
Fast Rates for Maximum Entropy Exploration. ICML (2023)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
Model-free Posterior Sampling via Learning Rate Randomization. NeurIPS (2023)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees. NeurIPS (2022)
Daniil Tiapkin, Alexander V. Gasnikov
Primal-Dual Stochastic Mirror Descent for MDPs. AISTATS (2022)
Daniil Tiapkin, Alexander V. Gasnikov, Pavel E. Dvurechensky
Stochastic saddle-point optimization for the Wasserstein barycenter problem. Optim. Lett. 16 (7) (2022)
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees. CoRR (2022)
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 (2022)
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. ICML (2022)
Darina Dvinskikh, Daniil Tiapkin
Improved Complexity Bounds in Wasserstein Barycenter Problem. AISTATS (2021)
Daniil Tiapkin, Alexander V. Gasnikov, Pavel E. Dvurechensky
Stochastic Saddle-Point Optimization for Wasserstein Barycenters. CoRR (2020)