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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：51/0  |  提交时间：2022/12/26
Big data  clustering  fuzzy double c-means  incomplete data  latent factor analysis  local feature weights.  
Generalized Nesterov's Acceleration-Incorporated, Non-Negative and Adaptive Latent Factor Analysis 期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 卷号: 15, 期号: 5, 页码: 2809-2823
作者:  Luo, Xin;  Zhou, Yue;  Liu, Zhigang;  Hu, Lun;  Zhou, MengChu
收藏  |  浏览/下载：78/0  |  提交时间：2022/12/26
Computational modeling  Acceleration  Sparse matrices  Adaptation models  Training  Data models  Convergence  Services computing  service application  big data  latent factor analysis  non-negative latent factor model  high-dimensional and sparse matrix  recommender system  missing data  
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  
Growing Echo State Network With an Inverse-Free Weight Update Strategy 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2022, 页码: 12
作者:  Chen, Xiufang;  Luo, Xin;  Jin, Long;  Li, Shuai;  Liu, Mei
收藏  |  浏览/下载：63/0  |  提交时间：2022/08/22
Reservoirs  Training  Computational modeling  Neurons  Topology  Standards  Numerical models  Echo state network (ESN)  inverse-free algorithm  incremental scheme  Schur complement  Sherman-Morrison formula  
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)  
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  
An alpha -beta -Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 13
作者:  Shang, Mingsheng;  Yuan, Ye;  Luo, Xin;  Zhou, MengChu
收藏  |  浏览/下载：54/0  |  提交时间：2022/08/22
Computational modeling  Sparse matrices  Convergence  Data models  Predictive models  Linear programming  Euclidean distance  -divergence  big data  convergence analysis  high-dimensional and sparse (HiDS) data  momentum  machine learning  missing data estimation  non-negative latent factor analysis (NLFA)  recommender system (RS)