Yulai Zhao

According to our database, Yulai Zhao authored at least 13 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review.

Masatoshi Uehara, Yulai Zhao, Chenyu Wang, Xiner Li, Aviv Regev, Sergey Levine, Tommaso Biancalani

CoRR, January, 2025

2024

Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding.

Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Aviv Regev, Sergey Levine, Masatoshi Uehara

CoRR, 2024

Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review.

Masatoshi Uehara, Yulai Zhao, Tommaso Biancalani, Sergey Levine

CoRR, 2024

Adding Conditional Control to Diffusion Models with Reinforcement Learning.

Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali

CoRR, 2024

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.

Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Tommaso Biancalani, Sergey Levine

CoRR, 2024

Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models.

Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani

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

Feedback Efficient Online Fine-Tuning of Diffusion Models.

Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani

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

Provably Efficient CVaR RL in Low-rank MDPs.

Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning.

Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee

Proceedings of the International Conference on Machine Learning, 2023

Blessing of Class Diversity in Pre-training.

Yulai Zhao, Jianshu Chen, Simon S. Du

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Optimizing the Performative Risk under Weak Convexity Assumptions.

Yulai Zhao

CoRR, 2022

Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games.

Yulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Provably Efficient Policy Gradient Methods for Two-Player Zero-Sum Markov Games.

Yulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du

CoRR, 2021