Chenjun Xiao
24 papers · 2019–2026 · 8 venues · across top CS/AI venues
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🗺️ Taxonomy Completionist (36) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Reinforcement Learning
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Machine Learning
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Optimization & Theory
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Artificial Intelligence
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Deep Learning
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Keywords
markov decision process
(4)
reinforcement learning
(4)
offline reinforcement learning
(3)
convergence rate
(3)
representation learning
(2)
temporal difference learning
(2)
policy learning
(2)
energy-based model
(2)
sample complexity
(2)
policy optimization
(2)
sample efficiency
(2)
function approximation
(2)
value function
(2)
tabular setting
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regret bound
(2)
diffusion model
(2)
behavior regularization
(2)
in-context learning
(1)
sequential decision making
(1)
policy gradient
(1)
Papers
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models (Abstract Reprint)
AAAI 2026
Large Language Model-Enhanced Multi-Armed Bandits
ACL 2026
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
ICML 2025
Diffusion Spectral Representation for Reinforcement Learning
NeurIPS 2024
Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration
NeurIPS 2024
HarmonyDream: Task Harmonization Inside World Models
ICML 2024
Iteratively Refined Behavior Regularization for Offline Reinforcement Learning
NeurIPS 2024
Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces
AAAI 2024
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning
ICML 2024
Rethinking Decision Transformer via Hierarchical Reinforcement Learning
ICML 2024
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
ICML 2024
Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning
UAI 2023
Energy-based Predictive Representations for Partially Observed Reinforcement Learning
UAI 2023
Latent Variable Representation for Reinforcement Learning
ICLR 2023
Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay
ICLR 2023
The In-Sample Softmax for Offline Reinforcement Learning
ICLR 2023
The Curse of Passive Data Collection in Batch Reinforcement Learning
AISTATS 2022
Understanding and Leveraging Overparameterization in Recursive Value Estimation
ICLR 2022
On the Optimality of Batch Policy Optimization Algorithms
ICML 2021
Understanding the Effect of Stochasticity in Policy Optimization
NeurIPS 2021
Escaping the Gravitational Pull of Softmax
NeurIPS 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods
ICML 2020
Maximum Entropy Monte-Carlo Planning
NeurIPS 2019
On Principled Entropy Exploration in Policy Optimization
IJCAI 2019