中国科学院重庆绿色智能技术研究院机构知识库

浏览/检索结果: 共20条，第1-10条

帮助

限定条件	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
	A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis 期刊论文 IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 3, 页码: 533-546 作者:  Wu, Hao;  Luo, Xin;  Zhou, MengChu;  Rawa, Muhyaddin J.;  Sedraoui, Khaled;  Albeshri, Aiiad 收藏  |  浏览/下载：54/0  |  提交时间：2022/08/22 Big data  high dimensional and incomplete (HDI) tensor  latent factorization-of-tensors (LFT)  machine learning  missing data  optimization  proportional-integral-derivative (PID) controller
	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
	A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 页码: 15 作者:  Wu, Di;  He, Yi;  Luo, Xin;  Zhou, MengChu 收藏  |  浏览/下载：44/0  |  提交时间：2022/08/22 Big data  computational intelligence  latent factor analysis (LFA)  missing data  online algorithm  online feature selection  sparse streaming feature  streaming feature
	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 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：82/0  |  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
	Robust Latent Factor Analysis for Precise Representation of High-Dimensional and Sparse Data 期刊论文 IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 4, 页码: 796-805 作者:  Wu, Di;  Luo, Xin 收藏  |  浏览/下载：82/0  |  提交时间：2021/05/17 High-dimensional and sparse matrix  L-1-norm  L-2-norm  latent factor model  recommender system  smooth L-1-norm
	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：54/0  |  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)
	Latent Factor-Based Recommenders Relying on Extended Stochastic Gradient Descent Algorithms 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 2, 页码: 916-926 作者:  Luo, Xin;  Wang, Dexian;  Zhou, MengChu;  Yuan, Huaqiang 收藏  |  浏览/下载：67/0  |  提交时间：2021/03/17 Big data  bi-linear  collaborative filtering (CF)  high-dimensional and sparse (HiDS) matrix  industry  latent factor (LF) analysis  missing data  recommender system
	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)