XUE, Ye
POSITION/TITLE
Research Scientist / Associate Research Fellow
Adjunct Assistant Professor, School of Data Science, CUHK(Shenzhen)
RESEARCH FIELD
Machine learning, non-convex optimization, online learning, federated learning, applications of artificial intelligence in communication networks, digital twins, and other interdisciplinary fields intersecting machine learning and communication.
PERSONAL WEBSITE
https://yokoxue.github.io/
EDUCATION BACKGROUND
The Hong Kong University of Science and Technology, PhD
Southeast University, Bachelor
BIOGRAPHY
Dr. Xue Ye obtained her bachelor's degree in Communication Engineering from Southeast University in 2017 and her PhD from the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology in 2022. She currently serves as an Associate Research Fellow at the Shenzhen Research Institute of Big Data and as an Assistant Professor (adjunct) at the School of Data Science at the Chinese University of Hong Kong (Shenzhen).
Her research interests lie at the intersection of non-convex optimization, high-dimensional statistics, machine learning, and communication networks. She has collaborated extensively with renowned scholars both domestically and internationally. In recent years, she has led projects funded by the National Natural Science Foundation of China's Youth Program and the National Key R&D Program of China, focusing on areas such as data-driven digital twin channel modeling and intelligent network optimization. As a core member, she has also participated in the Guangdong Major Project of Basic and Applied Basic Research.
Dr. Xue's research outcomes have been published in top-tier international journals and conferences, including IEEE Transactions on Signal Processing, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Wireless Communications, the International Conference on Learning Representations (ICLR), and the Conference on Uncertainty in Artificial Intelligence (UAI), among others.
ACADEMIC PUBLICATIONS
- Duanyi YAO, Songze Li, Ye Xue, Jin Liu, “Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit”, International Conference on Learning Representations (ICLR), 2024
- Y. Xue and V. Lau, “Riemannian Low-Rank Model Compression for Federated Learning with Over-the-Air Aggregation” IEEE Transactions on Signal Processing, 2023
- Ye Xue; Vincent K. N. Lau ; Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method, IEEE Transactions on Neural Networks and Learning Systems, 2021, 1-15
- Ye Xue; Vincent K. N. Lau; Songfu Cai ; Efficient Sparse Coding Using Hierarchical Riemannian Pursuit, IEEE Transactions on Signal Processing, 2021, 69: 4069-4084
- Ye Xue; Yifei Shen; Vincent K. N. Lau; Jun Zhang; Khaled B. Letaief ; Blind Data Detection in Massive MIMO via ℓ₃-Norm Maximization Over the Stiefel Manifold, IEEE Transactions on Wireless Communications, 2021, 20(2): 1411-1424
- Y. Xue*, Y. Shen, J. Zhang, K. Letaief, and V. Lau, “Complete dictionary learning via ℓp-norm maximization,” Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:280-289, 2020. （Co-first Author）
