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Found 4 from your keywords: author=Sch?olkopf, Bernhard.
cover
Advances in neural information processing systems 19 :proceedings of the 2006…
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Sch?olkopf, Bernhard.NIPS (Conference)Platt, John C.Hofmann, Thomas.

The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.OCLC-licensed vendor bibliographic record.

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ISBN/ISSN
9780262256919
Collation
1 online resource (xxiv, 1643 pages) :illustrations.
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cover
Learning with kernels :support vector machines, regularization, optimization,…
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Sch?olkopf, Bernhard.Smola, Alexander J.

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by…

Edition
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ISBN/ISSN
9780262256933
Collation
1 online resource (xviii, 626 pages) :illustrations.
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Kernel methods in computational biology
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Sch?olkopf, Bernhard.Tsuda, Koji.Vert, Jean-Philippe.

"A Bradford book."Modern machine learning techniques are proving to be extremely valuable for the analysis of data in computational biology problems. One branch of machine learning, kernel methods, lends itself particularly well to the difficult aspects of biological data, which include high dimensionality (as in microarray measurements), representation as discrete and structured data (as in DN…

Edition
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ISBN/ISSN
0262256924
Collation
1 online resource (ix, 400 pages) :illustrations.
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cover
Semi-supervised learning
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Chapelle, Olivier.Sch?olkopf, Bernhard.Zien, Alexander.

A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems, this text looks at state-of-the-art algorithms, applications benchmark experiments, and directions for future research.OCLC-licensed vendor bibliographic record.

Edition
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ISBN/ISSN
9780262255899
Collation
1 online resource (x, 508 pages) :illustrations.
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