Support Vector Machines - and other kernel-based learning methods
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Support Vector Machines and other kernel-based learning methods
John Shawe-Taylor & Nello Cristianini - Cambridge University Press, 2000 - Ordering Info »

About the Authors

Nello Cristianini

Nello Cristianini is a Professor of Artificial Intelligence at the University of Bristol since March 2006, and a holder of the Royal Society Wolfson Merit Award. He has wide research interests in the area of computational pattern analysis and its application to problems ranging from genomics, to computational linguistics and artificial intelligence systems. He has contributed extensively to the field of kernel methods. Before the appointment to Bristol he has held faculty positions at the University of California, Davis, and visiting positions at the University of California, Berkeley, and in many other institutions. Before that he was a research assistant at Royal Holloway, University of London. He has also covered industrial positions. He has a PhD from the University of Bristol, a MSc from Royal Holloway, University of London, and a Degree in Physics from University of Trieste. Since 2001 has been Action Editor of the Journal of Machine Learning Research (JMLR), and since 2005 also Associate Editor of the Journal of Artificial Intelligence Research (JAIR). He is co-author of the books 'An Introduction to Support Vector Machines' and 'Kernel Methods for Pattern Analysis' with John Shawe-Taylor, and "Introduction to Computational Genomics" with Matt Hahn (all published by Cambridge University Press).

John Shawe-Taylor

John Shawe-Taylor is a Professor of Computational Statistics and Machine Learning at the University College London, and the Director of itsCentre for Computational Statistics and Machine Learning. He obtained a PhD in Mathematics at Royal Holloway, University of London in 1986. He subsequently completed an MSc in the Foundations of Advanced Information Technology at Imperial College. He was promoted to Professor of Computing Science in 1996. He has published over 150 research papers. He has pioneered the development of the well-founded approaches to Machine Learning inspired by statistical learning theory (including Support Vector Machine, Boosting and Kernel Principal Components Analysis) and has shown the viability of applying these techniques to document analysis and computer vision. He is co-author with Nello Cristianini of the books "An Introduction to Support Vector Machines" and "Kernel Methods for Pattern Analysis".

Photo of the authors