中国科学院重庆绿色智能技术研究院机构知识库

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限定条件	资助项目：National Natural Science Foundation of China[61772493]    资助项目：National Natural Science Foundation of China[91646114]

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	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：74/0  |  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：63/0  |  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：48/0  |  提交时间：2022/08/22 Web service  quality-of-service  latent factor analysis  posterior-neighborhood  regularization  cloud computing  big data
	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 收藏  |  浏览/下载：70/0  |  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
	Symmetric Nonnegative Matrix Factorization-Based Community Detection Models and Their Convergence Analysis 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13 作者:  Luo, Xin;  Liu, Zhigang;  Jin, Long;  Zhou, Yue;  Zhou, MengChu 收藏  |  浏览/下载：52/0  |  提交时间：2022/08/22 Detectors  Convergence  Symmetric matrices  Social networking (online)  Analytical models  Tuning  Computational modeling  Community detection  convergence analysis  graph regularization  nonnegative multiplicative update (NMU)  social network analysis  symmetric and nonnegative matrix factorization (SNMF)
	A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 7, 页码: 4285-4296 作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Zhou, MengChu 收藏  |  浏览/下载：202/0  |  提交时间：2021/08/20 Big data  deep model  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  recommender system (RS)
	Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 8, 页码: 4612-4623 作者:  Xin, Luo;  Yuan, Ye;  Zhou, MengChu;  Liu, Zhigang;  Shang, Mingsheng 收藏  |  浏览/下载：128/0  |  提交时间：2021/08/20 beta-divergence  big data  high-dimensional and sparse (HiDS) matrix  industrial application  learning algorithm  non-negative latent factor (NLF) analysis  recommender system
	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：79/0  |  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
	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：142/0  |  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
	Latent Factor-Based Recommenders Relying on Extended Stochastic Gradient Descent Algorithms 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 2, 页码: 916-926 作者:  Luo, Xin;  Wang, Dexian;  Zhou, MengChu;  Yuan, Huaqiang 收藏  |  浏览/下载：64/0  |  提交时间：2021/03/17 Big data  bi-linear  collaborative filtering (CF)  high-dimensional and sparse (HiDS) matrix  industry  latent factor (LF) analysis  missing data  recommender system
	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：99/0  |  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
	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
	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 收藏  |  浏览/下载：369/0  |  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
	An adaptive latent factor model via particle swarm optimization 期刊论文 NEUROCOMPUTING, 2019, 卷号: 369, 页码: 176-184 作者:  Wang, Qingxian;  Chen, Sili;  Luo, Xin 收藏  |  浏览/下载：96/0  |  提交时间：2020/08/24 Latent factor analysis  Particle swarm optimization  High-dimensional and sparse matrix  Stochastic gradient descent  Self-adaptive model
	A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction 期刊论文 NEUROCOMPUTING, 2019, 卷号: 367, 页码: 299-307 作者:  Wang, Qingxian;  Chen, Minzhi;  Shang, Mingsheng;  Luo, Xin 收藏  |  浏览/下载：443/0  |  提交时间：2019/12/03 Big Data  QoS prediction  Temporal-aware QoS prediction  Stochastic gradient descent  Latent factorization of tensors  Momentum method
	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)  |  收藏  |  浏览/下载：211/0  |  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：505/0  |  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
	A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 3, 页码: 909-920 作者:  Wu, Di;  Luo, Xin;  Wang, Guoyin;  Shang, Mingsheng;  Yuan, Ye;  Yan, Huyong 收藏  |  浏览/下载：211/0  |  提交时间：2018/06/04 Differential evolution (DE)  general framework  industrial application  positioning optimization  self-labeled  semi-supervised classification (SSC)