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» Evolving kernels for support vector machine classification
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ML
2010
ACM
181views Machine Learning» more  ML 2010»
14 years 10 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
NIPS
2001
15 years 1 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
83
Voted
ICASSP
2009
IEEE
15 years 6 months ago
Combining VTS model compensation and support vector machines
It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test da...
Mark J. F. Gales, Federico Flego
ESANN
2000
15 years 1 months ago
Support Vector Committee Machines
Abstract. This paper proposes a mathematical programming framew ork for combining SVMs with possibly di erent kernels. Compared to single SVMs, the advantage of this approach is tw...
Dominique Martinez, Gilles Millerioux
PR
2006
152views more  PR 2006»
14 years 11 months ago
Edit distance-based kernel functions for structural pattern classification
A common approach in structural pattern classification is to define a dissimilarity measure on patterns and apply a distance-based nearest-neighbor classifier. In this paper, we i...
Michel Neuhaus, Horst Bunke