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	出处：IEEE TRANSACTIONS ON CYBERNETICS

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 Kalman-Filter-Incorporated Latent Factor Analysis Model for Temporally Dynamic Sparse Data 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2022, 页码: 14 作者:  Yuan, Ye;  Luo, Xin;  Shang, Mingsheng;  Wang, Zidong 收藏  |  浏览/下载：63/0  |  提交时间：2022/08/22 Quality of service  Data models  Kalman filters  Estimation  Computational modeling  Web services  Heuristic algorithms  Alternating least squares (ALSs)  computational intelligence  data science  dynamic latent factor analysis (LFA)  dynamics  intelligent computing  Kalman filter  temporal pattern  Web service
	Growing Echo State Network With an Inverse-Free Weight Update Strategy 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2022, 页码: 12 作者:  Chen, Xiufang;  Luo, Xin;  Jin, Long;  Li, Shuai;  Liu, Mei 收藏  |  浏览/下载：62/0  |  提交时间：2022/08/22 Reservoirs  Training  Computational modeling  Neurons  Topology  Standards  Numerical models  Echo state network (ESN)  inverse-free algorithm  incremental scheme  Schur complement  Sherman-Morrison formula
	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：121/0  |  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
	Temporal Pattern-Aware QoS Prediction via Biased Non-Negative Latent Factorization of Tensors 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1798-1809 作者:  Luo, Xin;  Wu, Hao;  Yuan, Huaqiang;  Zhou, MengChu 收藏  |  浏览/下载：371/0  |  提交时间：2020/08/24 Quality of service  Hidden Markov models  Data models  Training  Web services  Time factors  Latent factor analysis (LFA)  latent factorization of tensor  learning temporal pattern  linear bias (LB)  non-negative latent factorization of tensor  non-negativity constraint  quality-of-service (QoS) prediction
	Highly Efficient Framework for Predicting Interactions Between Proteins 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 3, 页码: 731-743 作者:  You, Zhu-Hong;  Zhou, MengChu;  Luo, Xin;  Li, Shuai Adobe PDF(1407Kb)  |  收藏  |  浏览/下载：216/0  |  提交时间：2018/03/15 Big data  feature extraction  kernel extreme learning machine (K-ELM)  low-rank approximation (LRA)  protein-protein interactions (PPIs)  support vector machine (SVM)