| Phase Transitions in Machine Learning Contributor(s): Saitta, Lorenza (Author), Giordana, Attilio (Author), Cornuéjols, Antoine (Author) |
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ISBN: 0521763916 ISBN-13: 9780521763912 Publisher: Cambridge University Press OUR PRICE: $107.35 Product Type: Hardcover - Other Formats Published: July 2011 |
| Additional Information |
| BISAC Categories: - Computers | Computer Vision & Pattern Recognition |
| Dewey: 006.31 |
| LCCN: 2011015141 |
| Physical Information: 1.1" H x 7.6" W x 9.9" (2.20 lbs) 410 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Phase transitions typically occur in combinatorial computational problems and have important consequences, especially with the current spread of statistical relational learning as well as sequence learning methodologies. In Phase Transitions in Machine Learning the authors begin by describing in detail this phenomenon, and the extensive experimental investigation that supports its presence. They then turn their attention to the possible implications and explore appropriate methods for tackling them. Weaving together fundamental aspects of computer science, statistical physics and machine learning, the book provides sufficient mathematics and physics background to make the subject intelligible to researchers in AI and other computer science communities. Open research issues are also discussed, suggesting promising directions for future research. |
Contributor Bio(s): Giordana, Attilio: - Attilio Giordana is Full Professor of Computer Science at the University of Piemonte Orientale in Italy.Cornuejols, Antoine: - Lorenza Saitta is a Full Professor of Computer Science at the University of Piemonte Orientale in Italy.Saitta, Lorenza: - Antoine Cornuejols is Full Professor of Computer Science at the AgroParisTech Engineering School in Paris. |