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books
| book details |
Multi-aspect Learning: Methods and Applications
By (author) Richi Nayak, By (author) Khanh Luong
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| on special |
normal price: R 5 385.95
Price: R 5 116.95
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| book 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.
| product details |
Normally shipped |
Publisher | Springer International Publishing AG
Published date | 28 Jul 2023
Language |
Format | Hardback
Pages | 184
Dimensions | 235 x 155 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-3-0313-3559-4
Readership Age |
BISAC |
| other options |
Normally shipped |
Readership Age |
Normal Price | R 7 177.95
Price | R 6 818.95
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Paperback / softback
384 pages
was: R 295.95
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