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Mixture Models and Applications (Unsupervised and Semi-Supervised Learning) - Tapa blanda

 
9783030238780: Mixture Models and Applications (Unsupervised and Semi-Supervised Learning)
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ISBN 10: 3030238784 ISBN 13: 9783030238780
Editorial: Springer, 2020

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Nizar Bouguila received the engineer degree from the University of Tunis, Tunis, Tunisia, in 2000, and the M.Sc. and Ph.D. degrees in computer science from Sherbrooke University, Sherbrooke, QC, Canada, in 2002 and 2006, respectively. He is currently a Professor with the Concordia Institute for Information Systems Engineering (CIISE) at Concordia University, Montreal, Quebec, Canada. His research interests include image processing, machine learning, data mining, computer vision, and pattern recognition. Prof. Bouguila received the best Ph.D Thesis Award in Engineering and Natural Sciences from Sherbrooke University in 2007. He was awarded the prestigious Prix d’excellence de l’association des doyens des etudes superieures au Quebec (best Ph.D Thesis Award in Engineering and Natural Sciences in Quebec), and was a runner-up for the prestigious NSERC doctoral prize. He is the author or co-author of more than 200 publications in several prestigious journals and conferences. He is a regular reviewer for many international journals and serving as associate editor for several journals such as Pattern Recognition. Dr. Bouguila is a licensed Professional Engineer registered in Ontario, and a Senior Member of the IEEE. He is the holder of the Concordia University Research Chair.

Wentao Fan received his M.Sc. and Ph.D. degrees in electrical and computer engineering from Concordia University, Montreal, Quebec, Canada, in 2009 and 2014, respectively. He is currently an Associate Professor in the Department of Computer Science and Technology, Huaqiao University, Xiamen, China. His research interests include machine learning, computer vision, deep learning and pattern recognition.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2020
Idioma
Inglés
ISBN 10 
3030238784
ISBN 13 
9783030238780
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
355
Editor
Bouguila Nizar, Fan Wentao
Contacto del fabricante
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