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A Novel Approach to Large-Scale Dynamically Weighted Directed Network Representation 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 卷号: 44, 期号: 12, 页码: 9756-9773
作者:  Luo, Xin;  Wu, Hao;  Wang, Zhi;  Wang, Jianjun;  Meng, Deyu
收藏  |  浏览/下载:67/0  |  提交时间:2022/12/26
Tensors  Computational modeling  Numerical models  Data models  Convergence  Analytical models  Adaptation models  Dynamically weighted directed network  terminal interaction pattern analysis system  latent factorization of tensors  high dimensional and incomplete tensor  link prediction  representation learning  latent feature  
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:74/0  |  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  
A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 3, 页码: 533-546
作者:  Wu, Hao;  Luo, Xin;  Zhou, MengChu;  Rawa, Muhyaddin J.;  Sedraoui, Khaled;  Albeshri, Aiiad
收藏  |  浏览/下载:53/0  |  提交时间:2022/08/22
Big data  high dimensional and incomplete (HDI) tensor  latent factorization-of-tensors (LFT)  machine learning  missing data  optimization  proportional-integral-derivative (PID) controller  
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:50/0  |  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:52/0  |  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)  
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:212/0  |  提交时间:2019/01/17
Big data  Recommender systems  Collaborative filtering  Latent factor analysis  Elastic-net  Regularization  Latent factor distribution  
Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 卷号: 13, 期号: 6, 页码: 3098-3107
作者:  Luo, Xin;  Sun, Jianpei;  Wang, Zidong;  Li, Shuai;  Shang, Mingsheng
Adobe PDF(803Kb)  |  收藏  |  浏览/下载:426/0  |  提交时间:2018/03/05
Big data application  high-dimensional, and sparse (SHiDS) matrix  nonnegative latent factor (NLF) model  symmetry  undirected HiDS network  
Highly Efficient Framework for Predicting Interactions Between Proteins 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 3, 页码: 731-743
作者:  You, Zhu-Hong;  Zhou, MengChu;  Luo, Xin;  Li, Shuai
Adobe PDF(1407Kb)  |  收藏  |  浏览/下载:218/0  |  提交时间:2018/03/15
Big data  feature extraction  kernel extreme learning machine (K-ELM)  low-rank approximation (LRA)  protein-protein interactions (PPIs)  support vector machine (SVM)