← Authors

Chenjun Xiao

23 papers · 2019–2026 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (5) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (25) πŸ† Grand Slam 🀝 Dynamic Duo (12) 🧬 Topic Evolution πŸ—ƒοΈ Keyword Collector (71) πŸ’Ž Century Club (22) πŸ”₯ Unstoppable (7) ⚑ Prolific Year (5)

Conferences

ICML (7) NIPS (6) ICLR (4) AAAI (2) UAI (2) AISTATS (1) IJCAI (1)

Top co-authors

Dale Schuurmans (12) Bo Dai (10) Jincheng Mei (8) Csaba SzepesvΓ‘ri (5) Jianye Hao (4) Martin MΓΌller (4) Hongming Zhang (3) Han Wang (3) Tongzheng Ren (3) Yangchen Pan (3)

Keywords

convergence rate (3) markov decision process (3) reinforcement learning (3) representation learning (2) policy optimization (2) regret bound (2) tabular setting (2) energy-based model (2) policy learning (2) temporal difference learning (1) sequential decision making (1) function approximation (1) supervised learning (1) convergence analysis (1) sample efficiency (1) policy gradient (1) minimax optimization (1) maximum entropy (1) loss landscape (1) neural network optimization (1)

Papers

An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models (Abstract Reprint) AAAI 2026
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning ICML 2025
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation ICML 2024
Iteratively Refined Behavior Regularization for Offline Reinforcement Learning NIPS 2024
Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration NIPS 2024
Diffusion Spectral Representation for Reinforcement Learning NIPS 2024
Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces AAAI 2024
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning ICML 2024
HarmonyDream: Task Harmonization Inside World Models ICML 2024
Rethinking Decision Transformer via Hierarchical Reinforcement Learning ICML 2024
The In-Sample Softmax for Offline Reinforcement Learning ICLR 2023
Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay ICLR 2023
Latent Variable Representation for Reinforcement Learning ICLR 2023
Energy-based Predictive Representations for Partially Observed Reinforcement Learning UAI 2023
Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning UAI 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 NIPS 2021
On the Global Convergence Rates of Softmax Policy Gradient Methods ICML 2020
Escaping the Gravitational Pull of Softmax NIPS 2020
On Principled Entropy Exploration in Policy Optimization IJCAI 2019
Maximum Entropy Monte-Carlo Planning NIPS 2019