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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11条,第1-10条
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语种:英语
资助项目:Natural Science Foundation of Chongqing (China)[cstc2019jcyjjqX0013]
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Nonnegative Latent Factor Analysis-Incorporated and Feature-Weighted Fuzzy Double $c$-Means Clustering for Incomplete Data
期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 卷号: 30, 期号: 10, 页码: 4165-4176
作者:
Song, Yan
;
Li, Ming
;
Zhu, Zhengyu
;
Yang, Guisong
;
Luo, Xin
收藏
  |  
浏览/下载:63/0
  |  
提交时间:2022/12/26
Big data
clustering
fuzzy double c-means
incomplete data
latent factor analysis
local feature weights.
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 Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction
期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 卷号: 34, 期号: 6, 页码: 2525-2538
作者:
Wu, Di
;
Luo, Xin
;
Shang, Mingsheng
;
He, Yi
;
Wang, Guoyin
;
Wu, Xindong
收藏
  |  
浏览/下载:82/0
  |  
提交时间:2022/08/22
Web Service
quality-of-service
QoS
latent factor analysis
density peak
data-characteristic-aware
missing data
big data
topological neighborhood
noise data
service selection
data science
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
收藏
  |  
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
Advancing Non-Negative Latent Factorization of Tensors With Diversified Regularization Schemes
期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 卷号: 15, 期号: 3, 页码: 1334-1344
作者:
Wu, Hao
;
Luo, Xin
;
Zhou, Mengchu
收藏
  |  
浏览/下载:73/0
  |  
提交时间:2022/08/22
High-dimensional and sparse tensor
missing data
latent factor analysis
temporal pattern
non-negativity
non-negative latent factorization of tensor
regularization
ensemble
services computing
A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction
期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 卷号: 15, 期号: 2, 页码: 793-805
作者:
Wu, Di
;
He, Qiang
;
Luo, Xin
;
Shang, Mingsheng
;
He, Yi
;
Wang, Guoyin
收藏
  |  
浏览/下载:61/0
  |  
提交时间:2022/08/22
Web service
quality-of-service
latent factor analysis
posterior-neighborhood
regularization
cloud computing
big data
An Alternating-Direction-Method of Multipliers-Incorporated Approach to Symmetric Non-Negative Latent Factor Analysis
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:
Luo, Xin
;
Zhong, Yurong
;
Wang, Zidong
;
Li, Maozhen
收藏
  |  
浏览/下载:64/0
  |  
提交时间:2022/08/22
Symmetric matrices
Computational modeling
Data models
Analytical models
Training
Learning systems
Convergence
Alternating-direction-method of multipliers (ADMM)
learning system
missing data
non-negative latent factor analysis (NLFA)
symmetric high-dimensional and incomplete matrix (SHDI)
undirected weighted network
An L-1-and-L-2-Norm-Oriented Latent Factor Model for Recommender Systems
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:
Wu, Di
;
Shang, Mingsheng
;
Luo, Xin
;
Wang, Zidong
收藏
  |  
浏览/下载:50/0
  |  
提交时间:2022/08/22
High-dimensional and sparse (HiDS) matrix
latent factor (LF) analysis
L-1 norm
L-2 norm
recommender system (RS)
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
收藏
  |  
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)
A proportional-integral-derivative-incorporated stochastic gradient descent-based latent factor analysis model
期刊论文
NEUROCOMPUTING, 2021, 卷号: 427, 页码: 29-39
作者:
Li, Jinli
;
Yuan, Ye
;
Ruan, Tao
;
Chen, Jia
;
Luo, Xin
收藏
  |  
浏览/下载:104/0
  |  
提交时间:2021/03/17
Big data
Stochastic gradient descent
Proportional integral derivation
PID controller
High-dimensional and sparse matrix
Latent factor analysis