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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浏览/检索结果: 共6条，第1-6条

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限定条件	资助项目：National Natural Science Foundation of China[61772493]    作者：吴迪    第一作者

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
	A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction 期刊论文 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 卷号: 34, 期号: 6, 页码: 2525-2538 作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Wu, Xindong 收藏  |  浏览/下载：64/0  |  提交时间：2022/08/22 Web Service  quality-of-service  QoS  latent factor analysis  density peak  data-characteristic-aware  missing data  big data  topological neighborhood  noise data  service selection  data science
	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：41/0  |  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
	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：40/0  |  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)
	Robust Latent Factor Analysis for Precise Representation of High-Dimensional and Sparse Data 期刊论文 IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 4, 页码: 796-805 作者:  Wu, Di;  Luo, Xin 收藏  |  浏览/下载：81/0  |  提交时间：2021/05/17 High-dimensional and sparse matrix  L-1-norm  L-2-norm  latent factor model  recommender system  smooth L-1-norm
	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
	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：212/0  |  提交时间：2018/06/04 Differential evolution (DE)  general framework  industrial application  positioning optimization  self-labeled  semi-supervised classification (SSC)