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Multi-aspect Learning: Methods and Applications

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Comprehensive review of multi aspect data learning methods for unsupervised machine learning—enables in-depth understanding of the field
Covers state-of-the-art representation learning techniques for clustering—provides up-to-date knowledge for current research
Explores manifold learning and dimensionality reduction in multi view data—addresses key challenges in multi aspect data analysis
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Summarized by Shop

Format: Hardback
Length: 184 pages
Publication date: 28 July 2023
Publisher: Springer International Publishing AG

This book offers a detailed and comprehensive analysis of multi-aspect data learning, focusing especially on representation learning approaches for unsupervised machine learning.

Dimension: 235 x 155 (mm)
ISBN-13: 9783031335594
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Author: Richi Nayak, Khanh Luong
Publisher: Springer International Publishing AG
Publication Date: 28 July 2023
Format: Hardcover
Page Count: 184
Dimensions: 235 x 155 mm
ISBN-13: 9783031335594
Language: English

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Shulph Ink

Shulph Ink

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