976 search results - page 33 / 196 » Training of Support Vector Machines with Mahalanobis Kernels |
157
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AAAI
2006
15 years 7 months ago
2006
This paper presents data selection procedures for support vector machines (SVM). The purpose of data selection is to reduce the dataset by eliminating as many non support vectors ...
178
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CSL
2006
Springer
15 years 6 months ago
2006
Springer
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
166
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ML
2002
ACM
15 years 5 months ago
2002
ACM
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
168
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ICPR
2006
IEEE
16 years 7 months ago
2006
IEEE
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
147
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DAGM
2004
Springer
15 years 9 months ago
2004
Springer
The well-known and very simple MinOver algorithm is reformulated for incremental support vector classification with and without kernels. A modified proof for its O(t-1/2 ) converge...