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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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浏览/检索结果:
共9条,第1-9条
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资助项目:National Natural Science Foundation of China[61772493]
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Hierarchical Particle Swarm Optimization-incorporated Latent Factor Analysis for Large-Scale Incomplete Matrices
期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 6, 页码: 1524-1536
作者:
Chen, Jia
;
Luo, Xin
;
Zhou, Mengchu
收藏
  |  
浏览/下载:64/0
  |  
提交时间:2022/12/26
Adaptation models
Optimization
Convergence
Computational modeling
Sparse matrices
Particle swarm optimization
Big Data
Big data
latent factor analysis
particle swarm optimization
high-dimensional and sparse matrix
large-scale incomplete data
missing data estimation
industrial application
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
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
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: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)
A Fast Non-Negative Latent Factor Model Based on Generalized Momentum Method
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 1, 页码: 610-620
作者:
Luo, Xin
;
Liu, Zhigang
;
Li, Shuai
;
Shang, Mingsheng
;
Wang, Zidong
收藏
  |  
浏览/下载:102/0
  |  
提交时间:2021/03/17
Big data
high-dimensional and sparse (HiDS) matrix
latent factor (LF) analysis
missing data estimation
non-negative LF (NLF) model
recommender system
Improved Symmetric and Nonnegative Matrix Factorization Models for Undirected, Sparse and Large-Scaled Networks: A Triple Factorization-Based Approach
期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 卷号: 16, 期号: 5, 页码: 3006-3017
作者:
Song, Yan
;
Li, Ming
;
Luo, Xin
;
Yang, Guisong
;
Wang, Chongjing
收藏
  |  
浏览/下载:116/0
  |  
提交时间:2020/08/24
Computational modeling
Sparse matrices
Biological system modeling
Symmetric matrices
Matrix decomposition
Linear programming
Convergence
Big data
data analysis
latent factor
nonnegativity
sparse and large-scaled network
symmetry
triple-factorization
undirected
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:125/0
  |  
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
Elastic-net regularized latent factor analysis-based models for recommender systems
期刊论文
NEUROCOMPUTING, 2019, 卷号: 329, 页码: 66-74
作者:
Wang, Dexian
;
Chen, Yanbin
;
Guo, Junxiao
;
Shi, Xiaoyu
;
He, Chunlin
;
Luo, Xin
;
Yuan, Huaqiang
Adobe PDF(1965Kb)
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浏览/下载:213/0
  |  
提交时间:2019/01/17
Big data
Recommender systems
Collaborative filtering
Latent factor analysis
Elastic-net
Regularization
Latent factor distribution
An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications
期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022
作者:
Luo, Xin
;
Zhou, MengChu
;
Li, Shuai
;
Shang, MingSheng
收藏
  |  
浏览/下载:508/0
  |  
提交时间:2018/07/02
Big data
high-dimensional and sparse matrix
learning algorithms
missing-data estimation
nonnegative latent factor analysis
optimization methods recommender system