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中国科学院重庆绿色智能技术研究院机构知识库
KMS Chongqing Institute of Green and Intelligent Technology, CAS
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出处:IEEE TRANSACTIONS ON CYBERNETICS
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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
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浏览/下载:72/0
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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
Distributed and Time-Delayed k-Winner-Take-All Network for Competitive Coordination of Multiple Robots
期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2022, 页码: 12
作者:
Jin, Long
;
Liang, Siqi
;
Luo, Xin
;
Zhou, Mengchu
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浏览/下载:71/0
  |  
提交时间:2022/08/22
Mathematical models
Delay effects
Task analysis
Robot kinematics
Multi-robot systems
Robustness
Heuristic algorithms
Competitive coordination
distributed control
intelligent network
k-winner-take-all (kWTA)
multirobot system
optimization
time delay
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
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浏览/下载:75/0
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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
Robust k-WTA Network Generation, Analysis, and Applications to Multiagent Coordination
期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 13
作者:
Qi, Yimeng
;
Jin, Long
;
Luo, Xin
;
Shi, Yang
;
Liu, Mei
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浏览/下载:53/0
  |  
提交时间:2022/08/22
Task analysis
Robustness
Biological neural networks
Resource management
Dynamic scheduling
Convergence
Recurrent neural networks
Consensus filter
k-winner-take-all (k-WTA)
multiagent coordination
theoretical analysis
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
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浏览/下载:62/0
  |  
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
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浏览/下载:134/0
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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
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浏览/下载:382/0
  |  
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
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
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浏览/下载:528/0
  |  
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
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浏览/下载:231/0
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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)