Robust Latent Feature Learning for Incomplete Big Data

Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature...

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Detaylı Bibliyografya

Yazar:	Wu, Di (Yazar)
Müşterek Yazar:	SpringerLink (Online service)
Materyal Türü:	Elektronik Ekitap
Dil:	İngilizce
Baskı/Yayın Bilgisi:	Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edisyon:	1st ed. 2023.
Seri Bilgileri:	SpringerBriefs in Computer Science,
Konular:	Artificial intelligence > Data processing. Quantitative research. Data mining. Data Science. Data Analysis and Big Data. Data Mining and Knowledge Discovery.
Online Erişim:	https://doi.org/10.1007/978-981-19-8140-1
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