中文版 | English

在结果中检索

CSpace
（本次检索基于用户作品认领结果）

浏览/检索结果: 共9条，第1-9条 帮助

限定条件        
已选(0)清除 条数/页：   排序方式：
An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 6, 页码: 3522-3532
作者:  Luo, Xin;  Wang, Zidong;  Shang, Mingsheng
收藏  |  浏览/下载：80/0  |  提交时间：2021/08/20
High-dimensional and sparse (HiDS) data  industrial application  instance-frequency  non-negative latent factor analysis (NLFA)  recommender system  regularization  
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：145/0  |  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  
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1844-1855
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Hu, Lun;  Shang, Mingsheng
收藏  |  浏览/下载：123/0  |  提交时间：2020/08/24
Computational modeling  Data models  Sparse matrices  Linear programming  Training  Convergence  Analytical models  Alternating-direction-method of multipliers  high-dimensional and sparse matrix  industrial application  non-negative latent factor analysis  recommender system  
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：414/0  |  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：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  
Efficient extraction of non-negative latent factors from high-dimensional and sparse matrices in industrial applications 会议论文
16th IEEE International Conference on Data Mining, ICDM 2016, Barcelona, Catalonia, Spain, December 12, 2016 - December 15, 2016
作者:  Luo, Xin;  Shang, Mingsheng;  Li, Shuai
收藏  |  浏览/下载：55/0  |  提交时间：2018/03/16
Symmetric non-negative latent factor models for undirected large networks 会议论文
26th International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, VIC, Australia, August 19, 2017 - August 25, 2017
作者:  Luo, Xin;  Shang, Ming-Sheng
收藏  |  浏览/下载：64/0  |  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：110/0  |  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：875/1  |  提交时间：2018/03/15
Latent factors  non-negativity  matrix factorization  non-negative big sparse matrix  big data  recommender system