KERNELS FOR STRUCTURED DATA (Machine Perception and Artificial Intelligence) - Hardcover

Gartner, Thomas

Hardcover

ISBN 10: 9812814558 ISBN 13: 9789812814555

Publisher: World Scientific Publishing Company, 2008

Synopsis

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.

Edition details

• Publisher: World Scientific Publishing Company
• Publication date: 2008
• Language: English
• ISBN 10: 9812814558
• ISBN 13: 9789812814555
• Binding: Hardcover
• Number of pages: 216