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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  
A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 7, 页码: 4285-4296
作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Zhou, MengChu
收藏  |  浏览/下载：204/0  |  提交时间：2021/08/20
Big data  deep model  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  recommender system (RS)  
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：148/0  |  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  
A Fast Non-Negative Latent Factor Model Based on Generalized Momentum Method 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 1, 页码: 610-620
作者:  Luo, Xin;  Liu, Zhigang;  Li, Shuai;  Shang, Mingsheng;  Wang, Zidong
收藏  |  浏览/下载：101/0  |  提交时间：2021/03/17
Big data  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  missing data estimation  non-negative LF (NLF) model  recommender system  
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：124/0  |  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  
A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction 期刊论文
NEUROCOMPUTING, 2019, 卷号: 367, 页码: 299-307
作者:  Wang, Qingxian;  Chen, Minzhi;  Shang, Mingsheng;  Luo, Xin
收藏  |  浏览/下载：447/0  |  提交时间：2019/12/03
Big Data  QoS prediction  Temporal-aware QoS prediction  Stochastic gradient descent  Latent factorization of tensors  Momentum method  
Popularity and Novelty Dynamics in Evolving Networks 期刊论文
SCIENTIFIC REPORTS, 2018, 卷号: 8, 页码: 10
作者:  Abbas, Khushnood;  Shang, Mingsheng;  Abbasi, Alireza;  Luo, Xin;  Xu, Jian Jun;  Zhang, Yu-Xia
Adobe PDF(2105Kb)  |  收藏  |  浏览/下载：266/0  |  提交时间：2018/06/04
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：416/0  |  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：428/0  |  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  
Emerging trends in evolving networks: Recent behaviour dominant and non-dominant model 期刊论文
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2017, 卷号: 484, 页码: 506-515
作者:  Abbas, Khushnood;  Shang, Mingsheng;  Luo, Xin;  Abbasi, Alireza
Adobe PDF(2072Kb)  |  收藏  |  浏览/下载：102/0  |  提交时间：2018/03/05
Novelty  Evolving networks  Recommender systems  E-commerce  Collective behaviour  Trend prediction  Emerging behaviour