Constrained Reinforcement Learning via Policy Splitting. - Haoxian Chen 002; Henry Lam; Fengpei Li; Amirhossein Meisami (ACML, 2020)

Demystifying Orthogonal Monte Carlo and Beyond. - Han Lin; Haoxian Chen 002; Krzysztof Marcin Choromanski; Tianyi Zhang; Clement Laroche (NeurIPS, 2020)

Learning Prediction Intervals for Regression: Generalization and Calibration. - Haoxian Chen 002; Ziyi Huang; Henry Lam; Huajie Qian; Haofeng Zhang 002 (AISTATS, 2021)

Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set. - Yuanlu Bai; Tucker Balch; Haoxian Chen 002; Danial Dervovic; Henry Lam; Svitlana Vyetrenko (CoRR, 2021)

Graph Kernel Attention Transformers. - Krzysztof Choromanski; Han Lin; Haoxian Chen 002; Jack Parker-Holder (CoRR, 2021)

Hybrid Random Features. - Krzysztof Marcin Choromanski; Han Lin; Haoxian Chen 002; Arijit Sehanobish; Yuanzhe Ma; Deepali Jain; Jake Varley; Andy Zeng 001; Michael S. Ryoo; Valerii Likhosherstov; Dmitry Kalashnikov; Vikas Sindhwani; et al. (ICLR, 2022)

From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. - Krzysztof Choromanski; Han Lin; Haoxian Chen 002; Tianyi Zhang; Arijit Sehanobish; Valerii Likhosherstov; Jack Parker-Holder; Tamás Sarlós; Adrian Weller; Thomas Weingarten (ICML, 2022)

Pseudo-Bayesian Optimization. - Haoxian Chen 002; Henry Lam (CoRR, 2023)

Mallows-DPO: Fine-Tune Your LLM with Preference Dispersions. - Haoxian Chen 002; Hanyang Zhao; Henry Lam; David D. Yao; Wenpin Tang (CoRR, 2024)

Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning. - Hanyang Zhao; Haoxian Chen 002; Ji Zhang; David D. Yao; Wenpin Tang (CoRR, 2024)

Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate. - Fengpei Li; Haoxian Chen 002; Jiahe Lin; Arkin Gupta; Xiaowei Tan; Gang Xu; Yuriy Nevmyvaka; Agostino Capponi; Henry Lam (CoRR, 2024)

MallowsPO: Fine-Tune Your LLM with Preference Dispersions. - Haoxian Chen 002; Hanyang Zhao; Henry Lam; David D. Yao; Wenpin Tang (ICLR, 2025)

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning. - Hanyang Zhao; Haoxian Chen 002; Ji Zhang; David D. Yao; Wenpin Tang (CoRR, 2025)

Fine-Tuning Diffusion Generative Models via Rich Preference Optimization. - Hanyang Zhao; Haoxian Chen 002; Yucheng Guo; Genta Indra Winata; Tingting Ou; Ziyu Huang; David D. Yao; Wenpin Tang (CoRR, 2025)