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Modeling and Optimization of Sensitivity and Creep for Multi-Component Sensing Materials 期刊论文
NANOMATERIALS, 2023, 卷号: 13, 期号: 2, 页码: 21
作者:  Bi, Gangping;  Xiao, Bowen;  Lin, Yuanchang;  Yan, Shaoqiu;  Tang, Ying;  He, Songxiying;  Shang, Mingsheng;  He, Guotian
收藏  |  浏览/下载：509/0  |  提交时间：2023/04/06
RSM  SVR  NSGA-II  MWCNTs  MLG  Ni  magnetic field  sensitivity  creep  
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：146/0  |  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  
SLAs-aware online task scheduling based on deep reinforcement learning method in cloud environment 会议论文
21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019, Zhangjiajie, China, August 10, 2019 - August 12, 2019
作者:  Ran, Longyu;  Shi, Xiaoyu;  Shang, Mingsheng
收藏  |  浏览/下载：154/0  |  提交时间：2020/02/18
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
收藏  |  浏览/下载：508/0  |  提交时间：2018/07/02
Big data  high-dimensional and sparse matrix  learning algorithms  missing-data estimation  nonnegative latent factor analysis  optimization methods 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：415/0  |  提交时间：2019/06/26
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：101/0  |  提交时间：2018/03/05
Novelty  Evolving networks  Recommender systems  E-commerce  Collective behaviour  Trend prediction  Emerging behaviour  
Water eutrophication assessment based on rough set and multidimensional cloud model 期刊论文
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2017, 卷号: 164, 页码: 103-112
作者:  Yan, Huyong;  Wu, Di;  Huang, Yu;  Wang, Guoyin;  Shang, Mingsheng;  Xu, Jianjun;  Shi, Xiaoyu;  Shan, Kun;  Zhou, Botian;  Zhao, Yufei
Adobe PDF(2910Kb)  |  收藏  |  浏览/下载：114/0  |  提交时间：2018/03/05
Eutrophication  Rough set  Multidimensional cloud model  
Empirical analysis of collaborative filtering-based recommenders in temporally evolving 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:  Shi, Xiao-Yu;  Luo, Xin;  Shang, Ming-Sheng;  Cai, Xin-Yi
Adobe PDF(752Kb)  |  收藏  |  浏览/下载：102/0  |  提交时间：2018/03/16
Recommendation in evolving online networks 期刊论文
EUROPEAN PHYSICAL JOURNAL B, 2016, 卷号: 89, 期号: 2, 页码: 7
作者:  Hu, Xiao;  Zeng, An;  Shang, Ming-Sheng
Adobe PDF(385Kb)  |  收藏  |  浏览/下载：74/0  |  提交时间：2018/03/15
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