Feature and Dimensionality Reduction for Clustering with Deep Learning

£109.50

Feature and Dimensionality Reduction for Clustering with Deep Learning

Communications engineering / telecommunications Data mining Artificial intelligence Expert systems / knowledge-based systems Pattern recognition

Authors: Frederic Ros, Rabia Riad

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Collection: Unsupervised and Semi-Supervised Learning

Language: English

Published by: Springer

Published on: 21st December 2023

Format: LCP-protected ePub

ISBN: 9783031487439


Overview of Deep Neural Network Methods for Clustering

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.

Highlights and Structure

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.

Intended Audience

The book can be very helpful for young researchers, non-experts, and R&D AI engineers.

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