Learning Representation for Multi-View Data Analysis / Advanced Information and Knowledge Processing (PDF)
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This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers' understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal.
A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.
- Autoren: Zhengming Ding , Handong Zhao , Yun Fu
- 2018, 1st ed. 2019, 268 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030007340
- ISBN-13: 9783030007348
- Erscheinungsdatum: 06.12.2018
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 7.79 MB
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