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：Natural Science Foundation of Chongqing (China)[cstc2019jcyjjqX0013]

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序发表日期升序发表日期降序题名升序题名降序WOS被引频次升序WOS被引频次降序提交时间升序提交时间降序期刊影响因子升序期刊影响因子降序
	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
	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：42/0  |  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)
	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：95/0  |  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
	Large-Scale Affine Matrix Rank Minimization With a Novel Nonconvex Regularizer 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Wang, Zhi;  Liu, Yu;  Luo, Xin;  Wang, Jianjun;  Gao, Chao;  Peng, Dezhong;  Chen, Wu 收藏  |  浏览/下载：52/0  |  提交时间：2022/08/22 Minimization  Convergence  Tensors  Optimization  Analytical models  Data models  Data analysis  Inexact proximal step  low-rank minimization  matrix completion  novel nonconvex regularizer  robust principal component analysis (RPCA)  tensor completion
	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)