Tucker Decomposition Network: Expressive Power and Comparison. - Ye Liu 014; JunJun Pan; Michael K. Ng 001 (CoRR, 2019)

Multi-Domain Networks Association for Biological Data Using Block Signed Graph Clustering. - Ye Liu 014; Michael K. Ng 001; Stephen Wu 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Multiple graph semi-supervised clustering with automatic calculation of graph associations. - Ye Liu 014; Michael K. Ng 001; Hong Zhu 012 (Neurocomputing, 2021)

Orthogonal Nonnegative Tucker Decomposition. - Junjun Pan; Michael K. Ng 001; Ye Liu 014; Xiongjun Zhang; Hong Yan 001 (SIAM J. Sci. Comput., 2021)

Deep neural network compression by Tucker decomposition with nonlinear response. - Ye Liu 014; Michael K. Ng 001 (Knowl. Based Syst., 2022)

A new clustering algorithm for genes with multiple cancer diseases by self-consistent field iteration method. - Ye Liu 014; Michael K. Ng 001 (Netw. Model. Anal. Health Informatics Bioinform., 2022)

The Social Technology and Research (STAR) Lab in the University of Hong Kong. - Reynold Cheng; Chenhao Ma 001; Xiaodong Li 009; Yixiang Fang; Ye Liu 014; Victor Y. L. Wong; Esther Lee; Tai Hing Lam; Sai Yin Ho; Man Ping Wang; Weijie Gong; Wentao Ning; et al. (SIGMOD Rec., 2022)

Robust Multi-view Spectral Clustering with Auto-encoder for Preserving Information. - Xiaojie Wang; Ye Liu 014; Hongshan Pu; Yuchen Mou; Chaoxiong Lin (ICONIP (5), 2023)

Tucker network: Expressive power and comparison. - Ye Liu 014; Junjun Pan; Michael K. P. Ng 001 (Neural Networks, 2023)

Module-level Gene-drug Interaction Identification via Hierarchical Optimal Transport. - Ye Liu 014; Xiaojie Wang; Hongshan Pu; Jiazhou Chen; Hongmin Cai (BIBM, 2024)

Simultaneous Computation and Memory Efficient Zeroth-Order Optimizer for Fine-Tuning Large Language Models. - Fei Wang 032; Li Shen 008; Liang Ding 006; Chao Xue; Ye Liu 014; Changxing Ding (CoRR, 2024)

HeGAE-AC: Heterogeneous graph auto-encoder for attribute completion. - Yejia Chen; Ye Liu 014 (Knowl. Based Syst., 2024)

Multi-order graph clustering with adaptive node-level weight learning. - Ye Liu 014; Xuelei Lin; Yejia Chen; Reynold Cheng (Pattern Recognit., 2024)

Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining? - Fei Wang 032; Liang Ding 006; Jun Rao; Ye Liu 014; Li Shen 008; Changxing Ding (ACM Trans. Multim. Comput. Commun. Appl., 2024)

QSTGNN: Quaternion Spatio-Temporal Graph Neural Networks. - Ye Liu 014; Chaoxiong Lin; Yuchen Mou; Huaiguang Jiang; Hongmin Cai (IEEE Trans. Knowl. Data Eng., 2025)