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» Training of Support Vector Machines with Mahalanobis Kernels
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185
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DIS
2008
Springer
15 years 8 months ago
String Kernels Based on Variable-Length-Don't-Care Patterns
Abstract. We propose a new string kernel based on variable-lengthdon't-care patterns (VLDC patterns). A VLDC pattern is an element of ({}) , where is an alphabet and is the ...
Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Shu...
180
Voted
ACL
2006
15 years 7 months ago
Automatic Learning of Textual Entailments with Cross-Pair Similarities
In this paper we define a novel similarity measure between examples of textual entailments and we use it as a kernel function in Support Vector Machines (SVMs). This allows us to ...
Fabio Massimo Zanzotto, Alessandro Moschitti
151
Voted
JMLR
2008
140views more  JMLR 2008»
15 years 6 months ago
Aggregation of SVM Classifiers Using Sobolev Spaces
This paper investigates statistical performances of Support Vector Machines (SVM) and considers the problem of adaptation to the margin parameter and to complexity. In particular ...
Sébastien Loustau
ICIAP
2003
ACM
16 years 6 months ago
Old fashioned state-of-the-art image classification
In this paper we present a statistical learning scheme for image classification based on a mixture of old fashioned ideas and state of the art learning tools. We represent input i...
Annalisa Barla, Francesca Odone, Alessandro Verri
ICML
2009
IEEE
16 years 7 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou