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：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
	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：146/0  |  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：66/0  |  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
	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：213/0  |  提交时间：2019/01/17 Big data  Recommender systems  Collaborative filtering  Latent factor analysis  Elastic-net  Regularization  Latent factor distribution
	Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 卷号: 13, 期号: 6, 页码: 3098-3107 作者:  Luo, Xin;  Sun, Jianpei;  Wang, Zidong;  Li, Shuai;  Shang, Mingsheng Adobe PDF(803Kb)  |  收藏  |  浏览/下载：427/0  |  提交时间：2018/03/05 Big data application  high-dimensional, and sparse (SHiDS) matrix  nonnegative latent factor (NLF) model  symmetry  undirected HiDS network
	Highly Efficient Framework for Predicting Interactions Between Proteins 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 3, 页码: 731-743 作者:  You, Zhu-Hong;  Zhou, MengChu;  Luo, Xin;  Li, Shuai Adobe PDF(1407Kb)  |  收藏  |  浏览/下载：219/0  |  提交时间：2018/03/15 Big data  feature extraction  kernel extreme learning machine (K-ELM)  low-rank approximation (LRA)  protein-protein interactions (PPIs)  support vector machine (SVM)