株式会社極東書店トップ商品一覧Feature and Dimensionality Reduction for Clustering with Deep Learning. 2024 ed.

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Feature and Dimensionality Reduction for Clustering with Deep Learning. 2024 ed.

Feature and Dimensionality Reduction for Clustering with Deep Learning. 2024 ed.

・ISBN 978-3-031-48742-2 hard EUR 119.99

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お気に入り
著者・編者Ros, Frederic / Riad, Rabia,
シリーズ (Unsupervised and Semi-Supervised Learning)
出版社 (Springer International Publishing AG, SZ)
出版年月2024
ページ数268 pp.
言語ENG
ニュース番号<A01-91029>

解説

This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by "family" to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers.