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Books Books 1 - 10 of about 41 related to Advances in Kernel Methods: Support Vector Learning.   

Kernel Methods in Computational Biology

Bernhard Schölkopf, Koji Tsuda, Jean-Philippe Vert - Computers - 2004 - 400 pages
A detailed overview of current research in kernel methods and their application to computational biology.
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Learning with Kernels: Support Vector Machines, Regularization, Optimization ...

Bernhard Schölkopf, Alexander J. Smola - Computers - 2002 - 626 pages
A comprehensive introduction to Support Vector Machines and related kernel methods.
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Advances in Large Margin Classifiers

Alexander J. Smola - Computers - 2000 - 412 pages
The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths ...
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Advances in Neural Information Processing Systems 19: Proceedings of the ...

Bernhard Schölkopf, John Platt, Thomas Hofmann - Computers - 2007 - 1643 pages
Papers from the 2006 flagship meeting on neural computation, with contributions from physicists, neuroscientists, mathematicians, statisticians, and computer scientists.
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Handbook of Statistical Bioinformatics

Henry Horng-Shing Lu, Bernhard Schölkopf, Hongyu Zhao - Mathematics - 2011 - 630 pages
Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and ...
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Dimension Reduction: A Guided Tour

Christopher J. C. Burges - Computers - 2010 - 106 pages
Dimension reduction is the mapping of data to a lower dimensional space such that uninformative variance in the data is discarded, or such that a subspace in which the data ...
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Predicting Structured Data

Gökhan BakIr, Neural Information Processing Systems Foundation - Computers - 2007 - 348 pages
State-of-the-art algorithms and theory in a novel domain of machine learning,prediction when the output has structure.
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Least Squares Support Vector Machines

Johan A. K. Suykens, Tony Van Gestel, Jos De Brabanter - Mathematics - 2002 - 294 pages
This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and ...
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Learning and Soft Computing: Support Vector Machines, Neural Networks, and ...

Vojislav Kecman - Computers - 2001 - 541 pages
This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are ...
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