Huizhuo Yuan

According to our database¹, Huizhuo Yuan authored at least 22 papers between 2018 and 2025.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of three.

Timeline

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On csauthors.net:

Bibliography

2025

On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning.

[BibT_eX]

[DOI]

CoRR, May, 2025

Simultaneous Modeling of Protein Conformation and Dynamics via Autoregression.

[BibT_eX]

[DOI]

CoRR, May, 2025

Game-Theoretic Regularized Self-Play Alignment of Large Language Models.

[BibT_eX]

[DOI]

CoRR, March, 2025

Tensor Product Attention Is All You Need.

[BibT_eX]

[DOI]

CoRR, January, 2025

Self-Play Preference Optimization for Language Model Alignment.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Towards Simple and Provable Parameter-Free Adaptive Gradient Methods.

[BibT_eX]

[DOI]

CoRR, 2024

MARS: Unleashing the Power of Variance Reduction for Training Large Models.

[BibT_eX]

[DOI]

CoRR, 2024

Accelerated Preference Optimization for Large Language Model Alignment.

[BibT_eX]

[DOI]

Jiafan He

Huizhuo Yuan

Quanquan Gu

CoRR, 2024

Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Protein Conformation Generation via Force-Guided SE(3) Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Fast Sampling via De-randomization for Discrete Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2023

Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2020

Stochastic Recursive Momentum for Policy Gradient Methods.

[BibT_eX]

[DOI]

CoRR, 2020

Stochastic Modified Equations for Continuous Limit of Stochastic ADMM.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization.

[BibT_eX]

[DOI]

Huizhuo Yuan

Xiangru Lian

Ji Liu

CoRR, 2019

Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Object-Oriented State Abstraction in Reinforcement Learning for Video Games.

[BibT_eX]

[DOI]

Yu Chen

Huizhuo Yuan

Yujun Li

Proceedings of the IEEE Conference on Games, 2019

2018

SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction.

[BibT_eX]

[DOI]

Huizhuo Yuan

Jinzhu Jia

Zhanxing Zhu

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Huizhuo Yuan

Timeline

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