SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction. - Huizhuo Yuan; Jinzhu Jia; Zhanxing Zhu (ISBI, 2018)

Object-Oriented State Abstraction in Reinforcement Learning for Video Games. - Yu Chen; Huizhuo Yuan; Yujun Li (CoG, 2019)

Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory. - Huizhuo Yuan; Yuren Zhou; Chris Junchi Li; Qingyun Sun (ICML, 2019)

Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent. - Huizhuo Yuan; Xiangru Lian; Chris Junchi Li; Ji Liu 002; Wenqing Hu (NeurIPS, 2019)

Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization. - Huizhuo Yuan; Xiangru Lian; Ji Liu 002 (CoRR, 2019)

Stochastic Modified Equations for Continuous Limit of Stochastic ADMM. - Xiang Zhou; Huizhuo Yuan; Chris Junchi Li; Qingyun Sun (CoRR, 2020)

Stochastic Recursive Momentum for Policy Gradient Methods. - Huizhuo Yuan; Xiangru Lian; Ji Liu; Yuren Zhou (CoRR, 2020)

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning. - Zixiang Chen; Chris Junchi Li; Huizhuo Yuan; Quanquan Gu; Michael I. Jordan (ICLR, 2023)

Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization. - Chris Junchi Li; Huizhuo Yuan; Gauthier Gidel; Quanquan Gu; Michael I. Jordan (ICML, 2023)

Fast Sampling via De-randomization for Discrete Diffusion Models. - Zixiang Chen; Huizhuo Yuan; Yongqian Li; Yiwen Kou; Junkai Zhang; Quanquan Gu (CoRR, 2023)

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models. - Zixiang Chen; Yihe Deng; Huizhuo Yuan; Kaixuan Ji; Quanquan Gu (ICML, 2024)

Protein Conformation Generation via Force-Guided SE(3) Diffusion Models. - Yan Wang; Lihao Wang; Yuning Shen; Yiqun Wang; Huizhuo Yuan; Yue Wu; Quanquan Gu (ICML, 2024)

Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time. - Zixiang Chen; Huizhuo Yuan; Yongqian Li; Yiwen Kou; Junkai Zhang; Quanquan Gu (NeurIPS, 2024)

Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation. - Huizhuo Yuan; Zixiang Chen; Kaixuan Ji; Quanquan Gu (NeurIPS, 2024)

Accelerated Preference Optimization for Large Language Model Alignment. - Jiafan He; Huizhuo Yuan; Quanquan Gu (CoRR, 2024)

MARS: Unleashing the Power of Variance Reduction for Training Large Models. - Huizhuo Yuan; Yifeng Liu 004; Shuang Wu; Xun Zhou; Quanquan Gu (CoRR, 2024)

Towards Simple and Provable Parameter-Free Adaptive Gradient Methods. - Yuanzhe Tao; Huizhuo Yuan; Xun Zhou; Yuan Cao 006; Quanquan Gu (CoRR, 2024)

Self-Play Preference Optimization for Language Model Alignment. - Yue Wu; Zhiqing Sun; Huizhuo Yuan; Kaixuan Ji; Yiming Yang; Quanquan Gu (ICLR, 2025)

Tensor Product Attention Is All You Need. - Yifan Zhang; Yifeng Liu 004; Huizhuo Yuan; Zhen Qin; Yang Yuan; Quanquan Gu; Andrew Chi-Chih Yao (CoRR, 2025)

Game-Theoretic Regularized Self-Play Alignment of Large Language Models. - Xiaohang Tang; Sangwoong Yoon; Seongho Son; Huizhuo Yuan; Quanquan Gu; Ilija Bogunovic (CoRR, 2025)

Simultaneous Modeling of Protein Conformation and Dynamics via Autoregression. - Yuning Shen; Lihao Wang; Huizhuo Yuan; Yan Wang; Bangji Yang; Quanquan Gu (CoRR, 2025)

On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning. - Yifan Zhang; Yifeng Liu 004; Huizhuo Yuan; Yang Yuan; Quanquan Gu; Andrew C. Yao (CoRR, 2025)