A Proximal Alternating-direction-method-of-multipliers-based Nonnegative Latent Factor Model. - Fanghui Bi; Di Wu (ICBK, 2021)

A Two-Stream Light Graph Convolution Network-based Latent Factor Model for Accurate Cloud Service QoS Estimation. - Fanghui Bi; Tiantian He 001; Xin Luo 001 (ICDM, 2022)

Two-Stream Graph Convolutional Network-Incorporated Latent Feature Analysis. - Fanghui Bi; Tiantian He 001; Yuetong Xie; Xin Luo 001 (IEEE Trans. Serv. Comput., 2023)

Proximal Alternating-Direction-Method-of-Multipliers-Incorporated Nonnegative Latent Factor Analysis. - Fanghui Bi; Xin Luo 001; Bo Shen 001; Hongli Dong; Zidong Wang 001 (IEEE CAA J. Autom. Sinica, 2023)

SCG: A Novel Spatiotemporal Coupling Graph Convolutional Network-Incorporated Approach for Dynamic QoS Estimation. - Fanghui Bi; Tiantian He 001 (SMC, 2024)

Discrete Multi-View Feature Propagation Preserving Graph Clustering. - Zhixuan Duan; Zuo Wang; Fanghui Bi; Tiantian He 001 (SMC, 2024)

Graph Clustering with Cross-View Feature Propagation. - Zhixuan Duan; Zuo Wang; Fanghui Bi (CoRR, 2024)

A Novel Spatiotemporal Coupling Graph Convolutional Network. - Fanghui Bi (CoRR, 2024)

A Fast Nonnegative Autoencoder-Based Approach to Latent Feature Analysis on High-Dimensional and Incomplete Data. - Fanghui Bi; Tiantian He 001; Xin Luo 001 (IEEE Trans. Serv. Comput., 2024)

Graph Linear Convolution Pooling for Learning in Incomplete High-Dimensional Data. - Fanghui Bi; Tiantian He 001; Yew-Soon Ong; Xin Luo 001 (IEEE Trans. Knowl. Data Eng., 2025)