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Learning and IR

Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms

  • David J. C. MacKay

"...an impressive book, intended as a class text on the subject of the title but having the character and robustness of a focused encyclopedia. The presentation is finely detailed, well documented, and stocked with artistic flourishes."
Mathematical Reviews

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Kernel Methods for Pattern Analysis

Kernel Methods for Pattern Analysis

  • John Shawe-Taylor, Nello Cristianini

This book provides professionals with a large selection of algorithms, kernels and solutions ready for implementation and suitable for standard pattern discovery problems in fields such as bioinformatics, text analysis and image analysis. It also serves as an introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.

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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

  • Nello Cristianini, John Shawe-Taylor

"This book is an excellent introduction to this area... it is nicely organized, self-contained, and well written. The book is most suitable for the beginning graduate student in computer science."
Richard A Chechile, Journal of Mathematical Psychology

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Finding Out About

Finding Out About
A Cognitive Perspective on Search Engine Technology and the WWW

  • Richard K. Belew

"FOA is a comprehensive resource for teaching a programming-based information retrieval class. The text provides an integrated introduction to many topics in information retrieval with a strong emphasis on mathematical and machine learning models, as well as giving a clear account of implementation details for the programming assignments."
Information Retrieval

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