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» Data selection for support vector machine classifiers
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WSC
1998
14 years 11 months ago
ExpertFit: Total Support for Simulation Input Modeling
In this paper, we discuss the critical role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we expl...
Averill M. Law, Michael G. McComas
ICPR
2008
IEEE
15 years 11 months ago
A discrete-time parallel update algorithm for distributed learning
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Christian Bauckhage, Tansu Alpcan
ICML
2009
IEEE
15 years 10 months ago
Ranking interesting subgroups
Subgroup discovery is the task of identifying the top k patterns in a database with most significant deviation in the distribution of a target attribute Y . Subgroup discovery is ...
Stefan Rueping
ICML
2006
IEEE
15 years 10 months ago
A continuation method for semi-supervised SVMs
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
Olivier Chapelle, Mingmin Chi, Alexander Zien
JMLR
2006
131views more  JMLR 2006»
14 years 9 months ago
On Representing and Generating Kernels by Fuzzy Equivalence Relations
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Bernhard Moser