Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems. - Ye Yuan 014; Xin Luo 001; Mingsheng Shang 001; Xin-Yi Cai (ICNSC, 2017)

Performance of latent factor models with extended linear biases. - Jia Chen; Xin Luo 001; Ye Yuan 014; Mingsheng Shang 001; Zhong Ming 001; Zhang Xiong 001 (Knowl. Based Syst., 2017)

Performance of nonnegative latent factor models with β-distance functions in recommender systems. - Ye Yuan 014; Xin Luo 001 (ICNSC, 2018)

Effects of preprocessing and training biases in latent factor models for recommender systems. - Ye Yuan 014; Xin Luo 001; Mingsheng Shang 001 (Neurocomputing, 2018)

A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications. - Di Wu 056; Xin Luo 001; Guoyin Wang 001; Mingsheng Shang 001; Ye Yuan 014; Huyong Yan (IEEE Trans. Ind. Informatics, 2018)

Randomized latent factor model for high-dimensional and sparse matrices from industrial applications. - Mingsheng Shang 001; Xin Luo 001; Zhigang Liu 006; Jia Chen; Ye Yuan 014; MengChu Zhou (IEEE CAA J. Autom. Sinica, 2019)

Temporal Web Service QoS Prediction via Kalman Filter-Incorporated Latent Factor Analysis. - Ye Yuan 014; Mingsheng Shang 001; Xin Luo 001 (ECAI, 2020)

Adaptive Regularization-Incorporated Latent Factor Analysis. - Xin Luo 001; Ye Yuan 014; Di Wu 056 (ICKG, 2020)

Accelerated Latent Factor Analysis for Recommender Systems via PID Controller. - Jinli Li; Xuke Wu; Ye Yuan 014; Yajuan Wu; Kangkang Ma; Yue Zhou (ICNSC, 2020)

A Nonlinear Proportional Integral Derivative-Incorporated Stochastic Gradient Descent-based Latent Factor Model. - Jinli Li; Ye Yuan 014 (SMC, 2020)

A Generalized and Fast-converging Non-negative Latent Factor Model for Predicting User Preferences in Recommender Systems. - Ye Yuan 014; Xin Luo 001; Mingsheng Shang 001; Di Wu 056 (WWW, 2020)

Dynamic Community Detection via Kalman Filter-Incorporated Non-negative Matrix Factorization. - Xiao Ying Zhang; Ye Yuan 014 (ICNSC, 2021)

Hyper-parameter-evolutionary latent factor analysis for high-dimensional and sparse data from recommender systems. - Jiufang Chen; Ye Yuan 014; Tao Ruan; Jia Chen; Xin Luo 001 (Neurocomputing, 2021)

A proportional-integral-derivative-incorporated stochastic gradient descent-based latent factor analysis model. - Jinli Li; Ye Yuan 014; Tao Ruan; Jia Chen; Xin Luo 001 (Neurocomputing, 2021)

Non-Negative Latent Factor Model Based on β-Divergence for Recommender Systems. - Xin Luo 001; Ye Yuan 014; MengChu Zhou; Zhigang Liu 006; Mingsheng Shang 001 (IEEE Trans. Syst. Man Cybern. Syst., 2021)

Adaptive Latent Factor Analysis via Generalized Momentum-Incorporated Particle Swarm Optimization. - Jiufang Chen; Ye Yuan 014 (ICNSC, 2022)

A Nonlinear PID-Enhanced Adaptive Latent Factor Analysis Model. - Jinli Li; Ye Yuan 014 (ICNSC, 2022)

Graph Regularized Nonnegative Latent Factor Analysis Model for Temporal Link Prediction in Cryptocurrency Transaction Networks. - Yue Zhou; Zhigang Liu 006; Ye Yuan 014 (ICNSC, 2022)

Adaptive Divergence-based Non-negative Latent Factor Analysis. - Ye Yuan 014; Guangxiao Yuan; Renfang Wang; Xin Luo 001 (CoRR, 2022)

PI-NLF: A Proportional-Integral Approach for Non-negative Latent Factor Analysis. - Ye Yuan 014; Xin Luo 001 (CoRR, 2022)

A Node-collaboration-informed Graph Convolutional Network for Precise Representation to Undirected Weighted Graphs. - Ying Wang 138; Ye Yuan 014; Xin Luo 001 (CoRR, 2022)

A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices. - Ye Yuan 014; Qiang He 001; Xin Luo 001; Mingsheng Shang 001 (IEEE Trans. Big Data, 2022)

An α-β-Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences. - Mingsheng Shang 001; Ye Yuan 014; Xin Luo 001; MengChu Zhou (IEEE Trans. Cybern., 2022)

Position-Transitional Particle Swarm Optimization-Incorporated Latent Factor Analysis. - Xin Luo 001; Ye Yuan 014; Sili Chen; Nianyin Zeng; Zidong Wang 001 (IEEE Trans. Knowl. Data Eng., 2022)

Latent Factor Analysis for High-dimensional and Sparse Matrices - A particle swarm optimization-based approach - Ye Yuan 014; Xin Luo 001 (Springer, 2022)

An Adaptive PID-Incorporated Non-Negative Latent Factor Analysis Model. - Jinli Li; ChengXuan Zhou; Ye Yuan 014 (ICDM (Workshops), 2023)

A Neighbor-Induced Graph Convolution Network for Undirected Weighted Network Representation. - Jiufang Chen; Ye Yuan 014 (SMC, 2023)

A Kalman-Filter-Incorporated Latent Factor Analysis Model for Temporally Dynamic Sparse Data. - Ye Yuan 014; Xin Luo 001; Mingsheng Shang 001; Zidong Wang 001 (IEEE Trans. Cybern., 2023)

An Adaptive Divergence-Based Non-Negative Latent Factor Model. - Ye Yuan 014; Renfang Wang; Guangxiao Yuan; Xin Luo 001 (IEEE Trans. Syst. Man Cybern. Syst., 2023)

An ADRC-Incorporated Stochastic Gradient Descent Algorithm for Latent Factor Analysis. - Jinli Li; Ye Yuan 014 (CoRR, 2024)

Adaptive Divergence-Based Non-Negative Latent Factor Analysis of High-Dimensional and Incomplete Matrices From Industrial Applications. - Ye Yuan 014; Xin Luo 001; MengChu Zhou (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

Pseudo Gradient-Adjusted Particle Swarm Optimization for Accurate Adaptive Latent Factor Analysis. - Xin Luo 001; Jiufang Chen; Ye Yuan 014; Zidong Wang 001 (IEEE Trans. Syst. Man Cybern. Syst., 2024)

SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks. - Jiufang Chen; Ye Yuan 014; Xin Luo 001 (IEEE CAA J. Autom. Sinica, 2024)

A Nonlinear PID-Incorporated Adaptive Stochastic Gradient Descent Algorithm for Latent Factor Analysis. - Jinli Li; Xin Luo 001; Ye Yuan 014; Shangce Gao (IEEE Trans Autom. Sci. Eng., 2024)

A Fuzzy PID-Incorporated Stochastic Gradient Descent Algorithm for Fast and Accurate Latent Factor Analysis. - Ye Yuan 014; Jinli Li; Xin Luo 001 (IEEE Trans. Fuzzy Syst., 2024)

A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data. - Jiufang Chen; Kechen Liu; Xin Luo 001; Ye Yuan 014; Khaled Sedraoui; Yusuf Al-Turki 001; MengChu Zhou (IEEE CAA J. Autom. Sinica, 2024)

Enhancing graph convolutional networks with an efficient k-hop neighborhood approach. - Jiufang Chen; Xin Luo 001; Ye Yuan 014; Zidong Wang 001 (Inf. Fusion, 2025)

A Proportional Integral Controller-Enhanced Non-Negative Latent Factor Analysis Model. - Ye Yuan 014; Siyang Lu; Xin Luo 001 (IEEE CAA J. Autom. Sinica, 2025)

A Node-Collaboration-Informed Graph Convolutional Network for Highly Accurate Representation to Undirected Weighted Graph. - Ye Yuan 014; Ying Wang 138; Xin Luo 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)