Kernels For Structured Data

Kernels For Structured Data

AngličtinaPevná väzba
Gartner, Thomas (Fraunhofer Iais, Germany)
World Scientific Publishing Co Pte Ltd
EAN: 9789812814555
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Podrobné informácie

This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by their atoms and bonds. The book guides the reader from the basics of kernel methods to advanced algorithms and kernel design for structured data. It is thus useful for readers who seek an entry point into the field as well as experienced researchers.
EAN 9789812814555
ISBN 9812814558
Typ produktu Pevná väzba
Vydavateľ World Scientific Publishing Co Pte Ltd
Dátum vydania 2. septembra 2008
Stránky 216
Jazyk English
Rozmery 235 x 160 x 19
Krajina Singapore
Čitatelia Postgraduate, Research & Scholarly
Autori Gartner, Thomas (Fraunhofer Iais, Germany)
Séria Series In Machine Perception And Artificial Intelligence