中国科学院重庆绿色智能技术研究院机构知识库

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限定条件	发表日期：2021    资助项目：National Natural Science Foundation of China[61772493]

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择期刊影响因子升序期刊影响因子降序作者升序作者降序题名升序题名降序WOS被引频次升序WOS被引频次降序发表日期升序发表日期降序提交时间升序提交时间降序
	An Alternating-Direction-Method of Multipliers-Incorporated Approach to Symmetric Non-Negative Latent Factor Analysis 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Luo, Xin;  Zhong, Yurong;  Wang, Zidong;  Li, Maozhen 收藏  |  浏览/下载：56/0  |  提交时间：2022/08/22 Symmetric matrices  Computational modeling  Data models  Analytical models  Training  Learning systems  Convergence  Alternating-direction-method of multipliers (ADMM)  learning system  missing data  non-negative latent factor analysis (NLFA)  symmetric high-dimensional and incomplete matrix (SHDI)  undirected weighted network
	Adjusting Learning Depth in Nonnegative Latent Factorization of Tensors for Accurately Modeling Temporal Patterns in Dynamic QoS Data 期刊论文 IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 卷号: 18, 期号: 4, 页码: 2142-2155 作者:  Luo, Xin;  Chen, Minzhi;  Wu, Hao;  Liu, Zhigang;  Yuan, Huaqiang;  Zhou, Mengchu 收藏  |  浏览/下载：83/0  |  提交时间：2021/11/26 Tensors  Data models  Quality of service  Computational modeling  Analytical models  Training  Web services  Algorithm  big data  dynamics  high-dimensional and incomplete (HDI) data  machine learning  missing data estimation  multichannel data  nonnegative latent factorization of tensors (NLFT)  temporal pattern  quality of service (QoS)  web service
	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)
	Convergence Analysis of Single Latent Factor-Dependent, Nonnegative, and Multiplicative Update-Based Nonnegative Latent Factor Models 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 4, 页码: 1737-1749 作者:  Liu, Zhigang;  Luo, Xin;  Wang, Zidong 收藏  |  浏览/下载：154/0  |  提交时间：2021/05/17 Manganese  Convergence  Computational modeling  Learning systems  Analytical models  Sparse matrices  Big Data  Big data  convergence  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  learning system  neural networks  nonnegative LF (NLF) analysis  single LF-dependent nonnegative and multiplicative update (SLF-NMU)
	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：55/0  |  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)
	Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning 期刊论文 IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 2, 页码: 402-411 作者:  Luo, Xin;  Qin, Wen;  Dong, Ani;  Sedraoui, Khaled;  Zhou, MengChu 收藏  |  浏览/下载：104/0  |  提交时间：2021/03/17 Big data  industrial application  industrial data  latent factor analysis  machine learning  parallel algorithm  recommender system (RS)  stochastic gradient descent (SGD)
	Symmetric Nonnegative Matrix Factorization-Based Community Detection Models and Their Convergence Analysis 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13 作者:  Luo, Xin;  Liu, Zhigang;  Jin, Long;  Zhou, Yue;  Zhou, MengChu 收藏  |  浏览/下载：54/0  |  提交时间：2022/08/22 Detectors  Convergence  Symmetric matrices  Social networking (online)  Analytical models  Tuning  Computational modeling  Community detection  convergence analysis  graph regularization  nonnegative multiplicative update (NMU)  social network analysis  symmetric and nonnegative matrix factorization (SNMF)
	Hyper-parameter-evolutionary latent factor analysis for high-dimensional and sparse data from recommender systems 期刊论文 NEUROCOMPUTING, 2021, 卷号: 421, 页码: 316-328 作者:  Chen, Jiufang;  Yuan, Ye;  Ruan, Tao;  Chen, Jia;  Luo, Xin 收藏  |  浏览/下载：75/0  |  提交时间：2021/02/24 Big Data  Intelligent Computation  Latent Factor Analysis  Evolutionary Computing  Learning Algorithm  High-dimensional and Sparse Data  Parameter Free