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124
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ICML
2005
IEEE
16 years 3 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
JMLR
2008
140views more  JMLR 2008»
15 years 2 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
100
Voted
NIPS
2001
15 years 3 months ago
A kernel method for multi-labelled classification
This article presents a Support Vector Machine (SVM) like learning system to handle multi-label problems. Such problems are usually decomposed into many two-class problems but the...
André Elisseeff, Jason Weston
90
Voted
AAAI
2007
15 years 4 months ago
Machine Learning for Automatic Mapping of Planetary Surfaces
We describe an application of machine learning to the problem of geomorphic mapping of planetary surfaces. Mapping landforms on planetary surfaces is an important task and the fi...
Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta
CONEXT
2007
ACM
15 years 4 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek