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：Pioneer Hundred Talents Program of Chinese Academy of Sciences

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择期刊影响因子升序期刊影响因子降序作者升序作者降序题名升序题名降序WOS被引频次升序WOS被引频次降序发表日期升序发表日期降序提交时间升序提交时间降序
	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
	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：79/0  |  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：75/0  |  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：72/0  |  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
	A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 页码: 15 作者:  Wu, Di;  He, Yi;  Luo, Xin;  Zhou, MengChu 收藏  |  浏览/下载：44/0  |  提交时间：2022/08/22 Big data  computational intelligence  latent factor analysis (LFA)  missing data  online algorithm  online feature selection  sparse streaming feature  streaming feature
	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：130/0  |  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
	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：154/0  |  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)
	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：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)
	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：67/0  |  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：101/0  |  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