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» On Combining Dissimilarity Representations
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ICML
2007
IEEE
14 years 7 months ago
On learning with dissimilarity functions
We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
Liwei Wang, Cheng Yang, Jufu Feng
BMCBI
2007
89views more  BMCBI 2007»
13 years 7 months ago
Combining dissimilarity based classifiers for cancer prediction using gene expression profiles
ent> <title> <p>Highlights from the Third International Society for Computational Biology (ISCB) Student Council Symposium at the Fifteenth Annual International Conf...
Ángela Blanco, Manuel Martín-Merino,...
CIARP
2007
Springer
14 years 1 months ago
Generalizing Dissimilarity Representations Using Feature Lines
A crucial issue in dissimilarity-based classification is the choice of the representation set. In the small sample case, classifiers capable of a good generalization and the inje...
Mauricio Orozco-Alzate, Robert P. W. Duin, C&eacut...

Publication
1763views
14 years 3 months ago
Reranking with Contextual dissimilarity measures from representational Bregman k-means
We present a novel reranking framework for Content Based Image Retrieval (CBIR) systems based on con-textual dissimilarity measures. Our work revisit and extend the method of Perro...
Olivier Schwander, Frank Nielsen
MCS
2010
Springer
13 years 9 months ago
A Multi-Classifier System for Off-Line Signature Verification Based on Dissimilarity Representation
Abstract. Although widely used to reduce error rates of difficult pattern recognition problems, multiple classifier systems are not in widespread use in off-line signature verifica...
Luana Batista, Eric Granger, Robert Sabourin