Téléchargez le livre : Multi-aspect Learning

Multi-aspect Learning

Methods and Applications de

,

Éditeur :

Springer


Paru le : 2023-07-27

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Description

This book offers a detailed and comprehensive analysis of multi-aspect data learning, focusing especially on representation learning approaches for unsupervised machine learning. It covers state-of-the-art representation learning techniques for clustering and their applications in various domains. This is the first book to systematically review multi-aspect data learning, incorporating a range of concepts and applications. Additionally, it is the first to comprehensively investigate manifold learning for dimensionality reduction in multi-view data learning. The book presents the latest advances in matrix factorization, subspace clustering, spectral clustering and deep learning methods, with a particular emphasis on the challenges and characteristics of multi-aspect data. Each chapter includes a thorough discussion of state-of-the-art of multi-aspect data learning methods and important research gaps. The book provides readers with the necessary foundational knowledge to apply these methods to new domains and applications, as well as inspire new research in this emerging field.
Pages
184 pages
Collection
n.c
Parution
2023-07-27
Marque
Springer
EAN papier
9783031335594
EAN PDF
9783031335600
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
18
Taille du fichier
5499 Ko
Prix
158,24 €
EAN EPUB
9783031335600
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
18
Taille du fichier
20736 Ko
Prix
158,24 €

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