Daniil Tiapkin
17 papers · 2021–2025 · 5 conferences · across top CS/AI conferences
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ICML (6)
AISTATS (5)
COLT (2)
ICLR (2)
NIPS (2)
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Keywords
markov decision process
(4)
bayesian inference
(2)
posterior sampling
(2)
stochastic optimization
(2)
regret bound
(2)
probabilistic modeling
(1)
non-convex optimization
(1)
temporal difference learning
(1)
optimal transport
(1)
bayesian reinforcement learning
(1)
primal-dual optimization
(1)
sample complexity
(1)
distributed learning
(1)
policy learning
(1)
dirichlet process
(1)
regret minimization
(1)
computational complexity
(1)
policy optimization
(1)
gradient descent
(1)
policy evaluation
(1)
Papers
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization
AISTATS 2025
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
ICLR 2025
Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games
ICML 2025
Revisiting Non-Acyclic GFlowNets in Discrete Environments
ICML 2025
On Teacher Hacking in Language Model Distillation
ICML 2025
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents
AISTATS 2025
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability
COLT 2024
Generative Flow Networks as Entropy-Regularized RL
AISTATS 2024
Demonstration-Regularized RL
ICLR 2024
Incentivized Learning in Principal-Agent Bandit Games
ICML 2024
Model-free Posterior Sampling via Learning Rate Randomization
NIPS 2023
Fast Rates for Maximum Entropy Exploration
ICML 2023
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold
COLT 2023
Primal-Dual Stochastic Mirror Descent for MDPs
AISTATS 2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
ICML 2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
NIPS 2022
Improved Complexity Bounds in Wasserstein Barycenter Problem
AISTATS 2021