CSpace
(本次检索基于用户作品认领结果)

浏览/检索结果: 共6条,第1-6条 帮助

限定条件            
已选(0)清除 条数/页:   排序方式:
Dynamic Neural Network for Bicriteria Weighted Control of Robot Manipulators 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Liu, Mei;  He, Li;  Shang, Mingsheng
收藏  |  浏览/下载:54/0  |  提交时间:2022/08/22
Manipulators  Robots  Indexes  Mathematical models  Manipulator dynamics  Optimization  Kinematics  Bicriteria weighted (BCW) scheme  dynamic neural network (DNN)  quadratic programming (QP) problem  robustness  
Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 8, 页码: 4612-4623
作者:  Xin, Luo;  Yuan, Ye;  Zhou, MengChu;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载:130/0  |  提交时间:2021/08/20
beta-divergence  big data  high-dimensional and sparse (HiDS) matrix  industrial application  learning algorithm  non-negative latent factor (NLF) analysis  recommender system  
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)  
An L-1-and-L-2-Norm-Oriented Latent Factor Model for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Wang, Zidong
收藏  |  浏览/下载:42/0  |  提交时间:2022/08/22
High-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  L-1 norm  L-2 norm  recommender system (RS)  
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)  
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:100/0  |  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