Huizhuo Yuan

According to our database1, Huizhuo Yuan authored at least 18 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2018
2019
2020
2021
2022
2023
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Towards Simple and Provable Parameter-Free Adaptive Gradient Methods.
CoRR, 2024

MARS: Unleashing the Power of Variance Reduction for Training Large Models.
CoRR, 2024

Accelerated Preference Optimization for Large Language Model Alignment.
CoRR, 2024

Self-Play Preference Optimization for Language Model Alignment.
CoRR, 2024

Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation.
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.
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.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Fast Sampling via De-randomization for Discrete Diffusion Models.
CoRR, 2023

Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization.
Proceedings of the International Conference on Machine Learning, 2023

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2020
Stochastic Recursive Momentum for Policy Gradient Methods.
CoRR, 2020

Stochastic Modified Equations for Continuous Limit of Stochastic ADMM.
CoRR, 2020

2019
Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization.
CoRR, 2019

Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

Object-Oriented State Abstraction in Reinforcement Learning for Video Games.
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.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018


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