Jiafan He
24 papers · 2019–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π Academic Marathon (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (7)
π
Cross-Pollinator
(7)
πΊοΈ
Taxonomy Completionist
(27)
π
Keyword Champion
(2)
π
Triple Crown
π¬
Deep Specialist
(12)
π€
Dynamic Duo
(23)
ποΈ
Keyword Collector
(70)
π₯
Unstoppable
(5)
π
Century Club
(24)
β‘
Prolific Year
(5)
Conferences
ICML (11)
NIPS (6)
ICLR (2)
ACML (1)
AISTATS (1)
COLT (1)
IJCAI (1)
UAI (1)
Top co-authors
Keywords
regret bound
(15)
reinforcement learning
(7)
linear function approximation
(6)
function approximation
(5)
markov decision process
(4)
linear bandit
(3)
minimax optimal
(3)
contextual bandit
(3)
linear mixture mdp
(3)
linear contextual bandit
(2)
online learning
(2)
minimax optimal regret
(2)
linear markov decision process
(2)
sample complexity
(2)
online algorithm
(2)
stochastic shortest path
(2)
eluder dimension
(2)
value iteration
(2)
upper confidence bound
(2)
asynchronous communication
(2)
Papers
Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback
ICML 2025
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
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
NIPS 2024
Achieving Constant Regret in Linear Markov Decision Processes
NIPS 2024
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual 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
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
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
ICML 2023
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits
ICML 2023
On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs
ICML 2022
Learning Stochastic Shortest Path with Linear Function Approximation
ICML 2022
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs
AISTATS 2022
Locally Differentially Private Reinforcement
Learning for Linear Mixture Markov Decision
Processes
ACML 2022
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits
NIPS 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
NIPS 2022
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
ICML 2021
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs
NIPS 2021
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
ICML 2021
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation
NIPS 2021
Achieving a Fairer Future by Changing the Past
IJCAI 2019