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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  
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:52/0  |  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)  
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  
Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 卷号: 48, 期号: 4, 页码: 1216-1228
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Xia, Yunni;  You, Zhu-Hong;  Zhu, QingSheng;  Leung, Hareton
收藏  |  浏览/下载:517/0  |  提交时间:2018/06/04
Big data  latent factor model  missing data prediction  quality-of-service (QoS)  second-order solver  service computing sparse matrices  Web service  
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)