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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  
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：53/0  |  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)  
Self-training semi-supervised classification based on density peaks of data 期刊论文
NEUROCOMPUTING, 2018, 卷号: 275, 页码: 180-191
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Xu, Ji;  Yan, Huyong;  Deng, Weihui;  Wang, Guoyin
收藏  |  浏览/下载：167/0  |  提交时间：2018/03/05
Density peaks  Self-training  Semi-supervised classification  Supervised learning  
An inherently nonnegative latent factor model for high-dimensional and sparse matrices from industrial applications 期刊论文
IEEE Transactions on Industrial Informatics, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022
作者:  Luo, Xin;  Zhou, Mengchu;  Li, Shuai;  Shang, Mingsheng
Adobe PDF(805Kb)  |  收藏  |  浏览/下载：415/0  |  提交时间：2019/06/26
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：427/0  |  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  
Nonlinearly-activated noise-tolerant zeroing neural network for distributed motion planning of multiple robot arms 会议论文
2017 International Joint Conference on Neural Networks, IJCNN 2017, Anchorage, AK, United states, May 14, 2017 - May 19, 2017
作者:  Jin, Long;  Li, Shuai;  Luo, Xin;  Shang, Ming-Sheng
Adobe PDF(2280Kb)  |  收藏  |  浏览/下载：98/0  |  提交时间：2018/03/16
Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems 会议论文
14th IEEE International Conference on Networking, Sensing and Control, ICNSC 2017, Calabria, Italy, May 16, 2017 - May 18, 2017
作者:  Yuan, Ye;  Luo, Xin;  Shang, Ming-Sheng;  Cai, Xin-Yi
Adobe PDF(717Kb)  |  收藏  |  浏览/下载：111/0  |  提交时间：2018/03/16
Performance of latent factor models with extended linear biases 期刊论文
Knowledge-Based Systems, 2017, 卷号: 123, 页码: 128-136
作者:  Chen, Jia;  Luo, Xin;  Yuan, Ye;  Shang, Mingsheng;  Ming, Zhong;  Xiong, Zhang
Adobe PDF(2755Kb)  |  收藏  |  浏览/下载：97/0  |  提交时间：2018/03/16
A Novel Approach to Extracting Non-Negative Latent Factors From Non-Negative Big Sparse Matrices 期刊论文
IEEE ACCESS, 2016, 卷号: 4, 页码: 2649-2655
作者:  Luo, Xin;  Zhou, Mengchu;  Shang, Mingsheng;  Li, Shuai;  Xia, Yunni
Adobe PDF(9487Kb)  |  收藏  |  浏览/下载：879/1  |  提交时间：2018/03/15
Latent factors  non-negativity  matrix factorization  non-negative big sparse matrix  big data  recommender system