About me

I’m a Ph.D. student advised by Prof. Mingrui Liu at Department of Computer Science, George Mason University since Spring 2023. Before that, I received my master’s degree in compuer science from University of Electronic Science and Technology of China, advised by William Zhu, and bachelor’s degree in EE from Sichuan University. I focus on designing efficient machine learning algorithms for practical problmes, including continual learning, meta-learning and large language model, and provide theoretical guatantees.

Research Interest

Bilevel Optimization, Continual Learning, Federated Learning, Parameter-Efficient Fine-Tuning for LLM.

(New!) (May 2024) One collaborative paper on bilevel optimization theory was accepted by ICML 2024.
(Jan 2024) One paper was accepted by ICLR 2024 Spotlight. Thanks to my advisor Mingrui and my collaborator Xiaochuan Gong.
(Sep 2023) One paper was accepted by Neurips 2023. Thanks to my advisor Mingrui and Kaiyi.
(Aug 2023) I will serve as a reviewer for AISTATS 2024.
(May 2023) One paper was accepted by UAI 2023.

(New!) A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
Xiaochuan Gong, Jie Hao, Mingrui Liu.
In the 41th International Conference on Machine Learning, 2024. (ICML 2024)
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
Jie Hao, Xiaochuan Gong, Mingrui Liu.
In the 12th International Conference on Learning Representations, 2024. (ICLR 2024) (Spotlight, 5% acceptance rate)
Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm
Jie Hao, Kaiyi Ji, Mingrui Liu.
In Advances in Neural Information Processing Systems 37, 2023. (NeurIPS 2023)
AUC Maximization in Imbalanced Lifelong Learning
Xiangyu Zhu, Jie Hao, Yunhui Guo, Mingrui Liu.
In the 39th Conference on Uncertainty in Artificial Intelligence, 2023. (UAI 2023)