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Hierarchical Particle Swarm Optimization-incorporated Latent Factor Analysis for Large-Scale Incomplete Matrices 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 6, 页码: 1524-1536
作者:  Chen, Jia;  Luo, Xin;  Zhou, Mengchu
收藏  |  浏览/下载：64/0  |  提交时间：2022/12/26
Adaptation models  Optimization  Convergence  Computational modeling  Sparse matrices  Particle swarm optimization  Big Data  Big data  latent factor analysis  particle swarm optimization  high-dimensional and sparse matrix  large-scale incomplete data  missing data estimation  industrial application  
Nonnegative Latent Factor Analysis-Incorporated and Feature-Weighted Fuzzy Double $c$-Means Clustering for Incomplete Data 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 卷号: 30, 期号: 10, 页码: 4165-4176
作者:  Song, Yan;  Li, Ming;  Zhu, Zhengyu;  Yang, Guisong;  Luo, Xin
收藏  |  浏览/下载：52/0  |  提交时间：2022/12/26
Big data  clustering  fuzzy double c-means  incomplete data  latent factor analysis  local feature weights.  
A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 3, 页码: 784-794
作者:  Yuan, Ye;  He, Qiang;  Luo, Xin;  Shang, Mingsheng
收藏  |  浏览/下载：75/0  |  提交时间：2022/08/22
Computational modeling  Sparse matrices  Big Data  Data models  Stochastic processes  Training  Software algorithms  Big data  latent factor analysis  generally multilayered structure  deep forest  multilayered extreme learning machine  randomized-learning  high-dimensional and sparse matrix  stochastic gradient descent  randomized model  
Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 2, 页码: 420-431
作者:  Shi, Xiaoyu;  He, Qiang;  Luo, Xin;  Bai, Yanan;  Shang, Mingsheng
收藏  |  浏览/下载：72/0  |  提交时间：2022/08/22
Recommender systems  Training  Optimization  Big Data  Cloud computing  Computational modeling  Sparse matrices  Recommender system  latent factor analysis  high-dimensional and sparse matrices  alternative stochastic gradient descent  distributed computing  
An Alternating-Direction-Method of Multipliers-Incorporated Approach to Symmetric Non-Negative Latent Factor Analysis 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:  Luo, Xin;  Zhong, Yurong;  Wang, Zidong;  Li, Maozhen
收藏  |  浏览/下载：56/0  |  提交时间：2022/08/22
Symmetric matrices  Computational modeling  Data models  Analytical models  Training  Learning systems  Convergence  Alternating-direction-method of multipliers (ADMM)  learning system  missing data  non-negative latent factor analysis (NLFA)  symmetric high-dimensional and incomplete matrix (SHDI)  undirected weighted network  
An L-1-and-L-2-Norm-Oriented Latent Factor Model for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Wang, Zidong
收藏  |  浏览/下载：42/0  |  提交时间：2022/08/22
High-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  L-1 norm  L-2 norm  recommender system (RS)  
Convergence Analysis of Single Latent Factor-Dependent, Nonnegative, and Multiplicative Update-Based Nonnegative Latent Factor Models 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 4, 页码: 1737-1749
作者:  Liu, Zhigang;  Luo, Xin;  Wang, Zidong
收藏  |  浏览/下载：154/0  |  提交时间：2021/05/17
Manganese  Convergence  Computational modeling  Learning systems  Analytical models  Sparse matrices  Big Data  Big data  convergence  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  learning system  neural networks  nonnegative LF (NLF) analysis  single LF-dependent nonnegative and multiplicative update (SLF-NMU)  
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2021, 卷号: 7, 期号: 1, 页码: 227-240
作者:  Luo, Xin;  Zhou, Mengchu;  Li, Shuai;  Wu, Di;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载：147/0  |  提交时间：2021/05/17
Data models  Training  Sparse matrices  Recommender systems  Computational modeling  Big Data  Scalability  Non-negative latent factor analysis  non-negativity  latent factor analysis  unconstrained optimization  high-dimensional and sparse matrix  collaborative filtering  recommender system  big data  
Large-Scale Affine Matrix Rank Minimization With a Novel Nonconvex Regularizer 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:  Wang, Zhi;  Liu, Yu;  Luo, Xin;  Wang, Jianjun;  Gao, Chao;  Peng, Dezhong;  Chen, Wu
收藏  |  浏览/下载：52/0  |  提交时间：2022/08/22
Minimization  Convergence  Tensors  Optimization  Analytical models  Data models  Data analysis  Inexact proximal step  low-rank minimization  matrix completion  novel nonconvex regularizer  robust principal component analysis (RPCA)  tensor completion  
Elastic-net regularized latent factor analysis-based models for recommender systems 期刊论文
NEUROCOMPUTING, 2019, 卷号: 329, 页码: 66-74
作者:  Wang, Dexian;  Chen, Yanbin;  Guo, Junxiao;  Shi, Xiaoyu;  He, Chunlin;  Luo, Xin;  Yuan, Huaqiang
Adobe PDF(1965Kb)  |  收藏  |  浏览/下载：213/0  |  提交时间：2019/01/17
Big data  Recommender systems  Collaborative filtering  Latent factor analysis  Elastic-net  Regularization  Latent factor distribution