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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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大数据挖掘及应用中心 [1]
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罗辛 [12]
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Parallel Adaptive Stochastic Gradient Descent Algorithms for Latent Factor Analysis of High-Dimensional and Incomplete Industrial Data
期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 页码: 14
作者:
Qin, Wen
;
Luo, Xin
;
Li, Shuai
;
Zhou, MengChu
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  |  
浏览/下载:26/0
  |  
提交时间:2023/12/25
Adaptation models
Training
Data models
Convergence
Stochastic processes
Sparse matrices
Tuning
Big data
latent factor analysis
Index Terms
adaptive model
parallelization
machine learning
stochastic gradient descent
high-dimensional and incomplete matrix
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
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  |  
浏览/下载:78/0
  |  
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
Generalized Nesterov's Acceleration-Incorporated, Non-Negative and Adaptive Latent Factor Analysis
期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 卷号: 15, 期号: 5, 页码: 2809-2823
作者:
Luo, Xin
;
Zhou, Yue
;
Liu, Zhigang
;
Hu, Lun
;
Zhou, MengChu
收藏
  |  
浏览/下载:101/0
  |  
提交时间:2022/12/26
Computational modeling
Acceleration
Sparse matrices
Adaptation models
Training
Data models
Convergence
Services computing
service application
big data
latent factor analysis
non-negative latent factor model
high-dimensional and sparse matrix
recommender system
missing data
A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices
期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 3, 页码: 784-794
作者:
Yuan, Ye
;
He, Qiang
;
Luo, Xin
;
Shang, Mingsheng
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  |  
浏览/下载:88/0
  |  
提交时间:2022/08/22
Computational modeling
Sparse matrices
Big Data
Data models
Stochastic processes
Training
Software algorithms
Big data
latent factor analysis
generally multilayered structure
deep forest
multilayered extreme learning machine
randomized-learning
high-dimensional and sparse matrix
stochastic gradient descent
randomized model
Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems
期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 2, 页码: 420-431
作者:
Shi, Xiaoyu
;
He, Qiang
;
Luo, Xin
;
Bai, Yanan
;
Shang, Mingsheng
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  |  
浏览/下载:83/0
  |  
提交时间:2022/08/22
Recommender systems
Training
Optimization
Big Data
Cloud computing
Computational modeling
Sparse matrices
Recommender system
latent factor analysis
high-dimensional and sparse matrices
alternative stochastic gradient descent
distributed computing
Convergence Analysis of Single Latent Factor-Dependent, Nonnegative, and Multiplicative Update-Based Nonnegative Latent Factor Models
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 4, 页码: 1737-1749
作者:
Liu, Zhigang
;
Luo, Xin
;
Wang, Zidong
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  |  
浏览/下载:164/0
  |  
提交时间:2021/05/17
Manganese
Convergence
Computational modeling
Learning systems
Analytical models
Sparse matrices
Big Data
Big data
convergence
high-dimensional and sparse (HiDS) matrix
latent factor (LF) analysis
learning system
neural networks
nonnegative LF (NLF) analysis
single LF-dependent nonnegative and multiplicative update (SLF-NMU)
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems
期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2021, 卷号: 7, 期号: 1, 页码: 227-240
作者:
Luo, Xin
;
Zhou, Mengchu
;
Li, Shuai
;
Wu, Di
;
Liu, Zhigang
;
Shang, Mingsheng
收藏
  |  
浏览/下载:160/0
  |  
提交时间:2021/05/17
Data models
Training
Sparse matrices
Recommender systems
Computational modeling
Big Data
Scalability
Non-negative latent factor analysis
non-negativity
latent factor analysis
unconstrained optimization
high-dimensional and sparse matrix
collaborative filtering
recommender system
big data
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:67/0
  |  
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 Novel Approximate Spectral Clustering Algorithm With Dense Cores and Density Peaks
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 页码: 13
作者:
Cheng, Dongdong
;
Huang, Jinlong
;
Zhang, Sulan
;
Zhang, Xiaohua
;
Luo, Xin
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2022/08/22
Clustering algorithms
Manifolds
Matrix decomposition
Sparse matrices
Partitioning algorithms
Approximation algorithms
Level measurement
Approximate spectral clustering
common neighborhood-based distance
dense cores
density peaks
geodesic distance
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:124/0
  |  
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