Haoxian Chen - RankMe

21 papers A* 5A 1C 1Journal 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Calibrating Non-Identifiable High-Dimensional Simulation Models: A Framework via Eligibility Set. ACM Trans. Model. Comput. Simul. Yuanlu Bai, Tucker Balch, Haoxian Chen, Danial Dervovic, Henry Lam, Svitlana Vyetrenko
2025	J	`jnl`	Fine-Tuning Diffusion Generative Models via Rich Preference Optimization. CoRR Hanyang Zhao, Haoxian Chen, Yucheng Guo, Genta Indra Winata, Tingting Ou, Ziyu Huang, David D. Yao, Wenpin Tang
2025	A*	`conf`	MallowsPO: Fine-Tune Your LLM with Preference Dispersions. ICLR Haoxian Chen, Hanyang Zhao, Henry Lam, David D. Yao, Wenpin Tang
2025	J	`jnl`	SOCRATES: Simulation Optimization with Correlated Replicas and Adaptive Trajectory Evaluations. CoRR Haoting Zhang, Haoxian Chen, Donglin Zhan, Hanyang Zhao, Henry Lam, Wenpin Tang, David D. Yao, Zeyu Zheng
2025	A*	`conf`	Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning. ICML Hanyang Zhao, Haoxian Chen, Ji Zhang, David D. Yao, Wenpin Tang
2025	J	`jnl`	Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning. CoRR Hanyang Zhao, Haoxian Chen, Ji Zhang, David D. Yao, Wenpin Tang
2025	J	`jnl`	Understanding Sampler Stochasticity in Training Diffusion Models for RLHF. CoRR Jiayuan Sheng, Hanyang Zhao, Haoxian Chen, David D. Yao, Wenpin Tang
2024	J	`jnl`	Mallows-DPO: Fine-Tune Your LLM with Preference Dispersions. CoRR Haoxian Chen, Hanyang Zhao, Henry Lam, David D. Yao, Wenpin Tang
2024	J	`jnl`	Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate. CoRR Fengpei Li, Haoxian Chen, Jiahe Lin, Arkin Gupta, Xiaowei Tan, Gang Xu, Yuriy Nevmyvaka, Agostino Capponi, Henry Lam
2024	J	`jnl`	Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning. CoRR Hanyang Zhao, Haoxian Chen, Ji Zhang, David D. Yao, Wenpin Tang
2023	J	`jnl`	Pseudo-Bayesian Optimization. CoRR Haoxian Chen, Henry Lam
2022	A*	`conf`	From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. ICML Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten
2022	A*	`conf`	Hybrid Random Features. ICLR Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael S. Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller
2021	J	`jnl`	Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set. CoRR Yuanlu Bai, Tucker Balch, Haoxian Chen, Danial Dervovic, Henry Lam, Svitlana Vyetrenko
2021	J	`jnl`	Graph Kernel Attention Transformers. CoRR Krzysztof Choromanski, Han Lin, Haoxian Chen, Jack Parker-Holder
2021	J	`jnl`	Hybrid Random Features. CoRR Krzysztof Choromanski, Haoxian Chen, Han Lin, Yuanzhe Ma, Arijit Sehanobish, Deepali Jain, Michael S. Ryoo, Jake Varley, Andy Zeng, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller
2021	A	`conf`	Learning Prediction Intervals for Regression: Generalization and Calibration. AISTATS Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang
2021	J	`jnl`	Learning Prediction Intervals for Regression: Generalization and Calibration. CoRR Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang
2020	C	`conf`	Constrained Reinforcement Learning via Policy Splitting. ACML Haoxian Chen, Henry Lam, Fengpei Li, Amirhossein Meisami
2020	A*	`conf`	Demystifying Orthogonal Monte Carlo and Beyond. NeurIPS Han Lin, Haoxian Chen, Krzysztof Marcin Choromanski, Tianyi Zhang, Clement Laroche
2020	J	`jnl`	Demystifying Orthogonal Monte Carlo and Beyond. CoRR Han Lin, Haoxian Chen, Tianyi Zhang, Clement Laroche, Krzysztof Choromanski