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This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Incorporating multiple views to improve the generalization performance, multiview learning is also known as data fusion or data integration from multiple feature sets.

This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This book describes the models and algorithms of multiview learning in real data analysis. Incorporating multiple views to improve the generalization performance, multiview learning is also known as data fusion or data integration from multiple feature sets. This self-contained book is applicable for multi-modal learning research, and requires minimal prior knowledge of the basic concepts in the field. It is also a valuable reference resource for researchers working in the field of machine learning and also those in various application domains.  

Boekdetails

Formaat
Hardback
Uitgever
Springer Verlag, Singapore
Imprint
Springer Verlag, Singapore
Auteur
Shiliang Sun || Liang Mao || Ziang Dong || Lidan Wu, Springer Verlag, Singapore, Springer Verlag, Singapore
ISBN-13
9789811330285
Verschijningsdatum
2019-01-17
Editie
2019 ed.
Afmetingen
155 mm × 235 mm
Land van herkomst
NL

Hardback

Multiview Machine Learning

door Shiliang Sun || Liang Mao || Ziang Dong || Lidan Wu

€ 187,74
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