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» Learning to learn with the informative vector machine
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MLDM
2005
Springer
16 years 5 days ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...
ALT
2003
Springer
16 years 3 months ago
Learning a Subclass of Regular Patterns in Polynomial Time
An algorithm for learning a subclass of erasing regular pattern languages is presented. On extended regular pattern languages generated by patterns π of the form x0α1x1 . . . α...
John Case, Sanjay Jain, Rüdiger Reischuk, Fra...
GPEM
2008
128views more  GPEM 2008»
15 years 6 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
ICML
2007
IEEE
16 years 7 months ago
Minimum reference set based feature selection for small sample classifications
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...
Xue-wen Chen, Jong Cheol Jeong
ICML
2008
IEEE
16 years 7 months ago
Robust matching and recognition using context-dependent kernels
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabariso...