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JMLR
2006
124views more  JMLR 2006»
13 years 8 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
COLT
2001
Springer
14 years 1 months ago
Limitations of Learning via Embeddings in Euclidean Half-Spaces
The notion of embedding a class of dichotomies in a class of linear half spaces is central to the support vector machines paradigm. We examine the question of determining the mini...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon
ML
2006
ACM
132views Machine Learning» more  ML 2006»
13 years 8 months ago
A suffix tree approach to anti-spam email filtering
We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and...
Rajesh Pampapathi, Boris Mirkin, Mark Levene
ICSM
2008
IEEE
14 years 3 months ago
Supporting software evolution analysis with historical dependencies and defect information
More than 90% of the cost of software is due to maintenance and evolution. Understanding the evolution of large software systems is a complex problem, which requires the use of va...
Marco D'Ambros
FLAIRS
2003
13 years 10 months ago
Optimizing F-Measure with Support Vector Machines
Support vector machines (SVMs) are regularly used for classification of unbalanced data by weighting more heavily the error contribution from the rare class. This heuristic techn...
David R. Musicant, Vipin Kumar, Aysel Ozgur