Mixture Models and Applications
Springer International Publishing
ISBN 978-3-030-23876-6
Standardpreis
Bibliografische Daten
eBook. PDF. Weiches DRM (Wasserzeichen)
2019
XII, 355 p. 120 illus., 88 illus. in color..
In englischer Sprache
Umfang: 355 S.
Verlag: Springer International Publishing
ISBN: 978-3-030-23876-6
Weiterführende bibliografische Daten
Das Werk ist Teil der Reihe: Unsupervised and Semi-Supervised Learning
Produktbeschreibung
This book focuses on recent advances, approaches, theories and applications related to mixture models. In particular, it presents recent unsupervised and semi-supervised frameworks that consider mixture models as their main tool. The chapters considers mixture models involving several interesting and challenging problems such as parameters estimation, model selection, feature selection, etc. The goal of this book is to summarize the recent advances and modern approaches related to these problems. Each contributor presents novel research, a practical study, or novel applications based on mixture models, or a survey of the literature.
- Reports advances on classic problems in mixture modeling such as parameter estimation, model selection, and feature selection;
- Present theoretical and practical developments in mixture-based modeling and their importance in different applications;
- Discusses perspectives and challenging future works related to mixture modeling.
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