Jiafan He
24 papers · 2019–2025 · 8 venues · across top CS/AI venues
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Achievements
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Research topics
Machine Learning
(23)
Optimization & Theory
(20)
Reinforcement Learning
(16)
Methods
(16)
Learning Types
(15)
Artificial Intelligence
(8)
Core AI
(8)
Mathematics & Optimization
(6)
Optimization
(6)
Application Areas
(2)
Core Methods
(2)
Deep Learning
(1)
Security & Privacy
(1)
Applications
(1)
Differential Privacy
(1)
Keywords
regret bound
(18)
reinforcement learning
(9)
linear function approximation
(7)
function approximation
(6)
linear mixture mdp
(4)
markov decision process
(4)
linear contextual bandit
(3)
linear bandit
(3)
minimax optimal
(3)
value iteration
(3)
contextual bandit
(3)
online learning
(2)
adversarial reward
(2)
minimax optimal regret
(2)
sample complexity
(2)
upper confidence bound
(2)
stochastic shortest path
(2)
eluder dimension
(2)
online algorithm
(2)
linear markov decision process
(2)
Papers
Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback
ICML 2025
Achieving Constant Regret in Linear Markov Decision Processes
NeurIPS 2024
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
NeurIPS 2024
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
ICLR 2024
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
ICLR 2024
Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption
ICML 2024
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
ICML 2023
Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path
ICML 2023
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes
ICML 2023
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
ICML 2023
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits
ICML 2023
Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension
UAI 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency
COLT 2023
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits
NeurIPS 2022
Learning Stochastic Shortest Path with Linear Function Approximation
ICML 2022
Locally Differentially Private Reinforcement
Learning for Linear Mixture Markov Decision
Processes
ACML 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
NeurIPS 2022
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs
AISTATS 2022
On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs
ICML 2022
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
ICML 2021
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs
NeurIPS 2021
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
ICML 2021
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation
NeurIPS 2021
Achieving a Fairer Future by Changing the Past
IJCAI 2019