Hello! I am Haoran Xu (εΎζ΅©ηΆ in Chinese). I am a first-year Ph.D. student at UT Austin, advised by Prof. Amy Zhang. Previously, I worked at Institute for AI Industry Research (AIR), Tsinghua University, Microsoft Research Asia and JD.com on data-driven Reinforcement Learning and its applications. I obtained Bachelor & Master's degree from Xidian University, advised by Xianyuan Zhan and Zheng Yu.
My ultimate research dream is to maximally leveraging prior information to facilitate the development of machine autonomy. Towards this goal, my work primarily focused on offline RL, imitation learning, hybrid RL, and RLHF. I am open to collaboration, feel free to reach me out!
Some links: CV / Github / Twitter / Google Scholar / haoran.xu@utexas.edu
News
- πΊπΈ I am attending NeurIPS 2023 in-person at New Orleans.
- One paper on offline multi-agent RL is accepted to NeurIPS 2023.
- π Starting my PhD at UT Austin.
- π·πΌ I am attending ICLR 2023 in-person at Kigali.
- π Three papers I like very much on offline RL and reward learning are accepted to ICLR 2023.
- Honored to be selected as Top Reviewers in NeurIPS 2022.
- One paper on offline RL is accepted to NeurIPS 2022.
- One paper on offline IL is accepted to ICML 2022.
Publications (* marks equal contribution)
- Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization ICLR 2023 (Oral, Top 5%) 2023 Paper | Code | Slides
- A Policy-Guided Imitation Approach for Offline Reinforcement Learning NeurIPS 2022 (Oral, Top 2%) 2023 Paper | Code | Slides | Media
- Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations ICML 2022 2022 Paper | Code | Slides
- Constraints Penalized Q-Learning for Safe Offline Reinforcement Learning AAAI 2022 (Spotlight @ ICML 2021 RL4RealLife workshop) 2022 Paper | Code | Slides
- DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning AAAI 2022 (Spotlight @ ICML 2021 RL4RealLife workshop) 2022 Paper | Code
- Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update Under review 2023 Paper |
- Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization NeurIPS 2023 2023 Paper | Code
- PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning Preprint, under review 2023 Paper | Code
- SaFormer: A Conditional Sequence Modeling Approach to Offline Safe Reinforcement Learning ICLR 2023 SR4AD Workshop 2023 Paper
- Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization ICLR 2023 (Notable Top 5%) 2023 Paper | Code
- Mind the Gap: Offline Policy Optimizaiton for Imperfect Rewards ICLR 2023 2023 Paper | Code
- When data geometry meets deep function: Generalizing offline reinforcement learning ICLR 2023 2023 Paper | Code
- A Policy-Guided Imitation Approach for Offline Reinforcement Learning NeurIPS 2022 (Oral, Top 2%) 2022 Paper | Code | Slides | Media
- Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations ICML 2022 2022 Paper | Code | Slides
- Constraints Penalized Q-Learning for Safe Offline Reinforcement Learning AAAI 2022 (Spotlight @ ICML 2021 RL4RealLife workshop) 2022 Paper | Code | Slides
- DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning AAAI 2022 (Spotlight @ ICML 2021 RL4RealLife workshop) 2022 Paper | Code
- Discriminator-Guided Model-Based Offline Imitation Learning CoRL 2022 2022 Paper
- Model-Based Offline Planning with Trajectory Pruning IJCAI 2022 2022 Paper | Code
- ECoalVis: Visual Analysis of Control Strategies in Coal-fired Power Plants IEEE VIS 2022 2022 Paper | Code
- Multi-Memory enhanced Separation Network for Indoor Temperature Prediction DASFAA 2022 2022 Paper
- Offline Reinforcement Learning with Soft Behavioral Regularization NeurIPS 2021 Offline RL Workshop 2021 Paper | Code
- Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning AAAI 2021 2021 Paper