964 search results - page 103 / 193 » Incremental and Decremental Support Vector Machine Learning |
108
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CVPR
2010
IEEE
15 years 4 months ago
2010
IEEE
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
101
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ICANN
2007
Springer
15 years 7 months ago
2007
Springer
Abstract. Classification of structured data (i.e., data that are represented as graphs) is a topic of interest in the machine learning community. This paper presents a different,...
111
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ECML
2006
Springer
15 years 5 months ago
2006
Springer
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
130
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KES
2008
Springer
15 years 1 months ago
2008
Springer
Abstract. This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting wellfounded kernel methods fo...
127
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IJPRAI
2010
15 years 23 hour ago
2010
: AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample...