Daniil Tiapkin
17 papers · 2021–2025 · 5 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (30) 🤝 Dynamic Duo (10) 🗃️ Keyword Collector (91)
🔥
Unstoppable · Bronze
⚡
Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(13)
Optimization & Theory
(10)
Reinforcement Learning
(9)
Learning Types
(9)
Methods
(9)
Artificial Intelligence
(5)
Core AI
(4)
Deep Learning
(3)
Mathematics & Optimization
(3)
Optimization
(3)
Applications
(2)
Models
(2)
Architectures
(1)
Bayesian & Probabilistic
(1)
Learning Paradigms
(1)
Keywords
markov decision process
(5)
sample complexity
(3)
regret bound
(3)
policy optimization
(3)
stochastic optimization
(2)
regret minimization
(2)
bayesian inference
(2)
posterior sampling
(2)
entropy-regularized reinforcement learning
(2)
reinforcement learning
(2)
generative flow network
(2)
communication complexity
(1)
probabilistic modeling
(1)
distributed learning
(1)
primal-dual optimization
(1)
non-convex optimization
(1)
optimal transport
(1)
bayesian reinforcement learning
(1)
dirichlet process
(1)
behavior cloning
(1)
Papers
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents
AISTATS 2025
Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games
ICML 2025
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization
AISTATS 2025
On Teacher Hacking in Language Model Distillation
ICML 2025
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
ICLR 2025
Revisiting Non-Acyclic GFlowNets in Discrete Environments
ICML 2025
Demonstration-Regularized RL
ICLR 2024
Generative Flow Networks as Entropy-Regularized RL
AISTATS 2024
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability
COLT 2024
Incentivized Learning in Principal-Agent Bandit Games
ICML 2024
Fast Rates for Maximum Entropy Exploration
ICML 2023
Model-free Posterior Sampling via Learning Rate Randomization
NeurIPS 2023
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold
COLT 2023
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
ICML 2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
NeurIPS 2022
Primal-Dual Stochastic Mirror Descent for MDPs
AISTATS 2022
Improved Complexity Bounds in Wasserstein Barycenter Problem
AISTATS 2021