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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	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 收藏  |  浏览/下载：13/0  |  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 收藏  |  浏览/下载：61/0  |  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：77/0  |  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 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
	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
	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：152/0  |  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：145/0  |  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：52/0  |  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 收藏  |  浏览/下载：122/0  |  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