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» Constraint Programming for Data Mining and Machine Learning
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ICML
2004
IEEE
16 years 3 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 9 months ago
Towards clustering with XCS
This paper presents a novel approach to clustering using an accuracy-based Learning Classifier System. Our approach achieves this by exploiting the generalization mechanisms inher...
Kreangsak Tamee, Larry Bull, Ouen Pinngern
ICML
2004
IEEE
15 years 8 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
GECCO
2003
Springer
117views Optimization» more  GECCO 2003»
15 years 8 months ago
A Method for Handling Numerical Attributes in GA-Based Inductive Concept Learners
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
Federico Divina, Maarten Keijzer, Elena Marchiori
BCS
2008
15 years 4 months ago
A Customisable Multiprocessor for Application-Optimised Inductive Logic Programming
This paper describes a customisable processor designed to accelerate execution of inductive logic programming, targeting advanced field-programmable gate array (FPGA) technology. ...
Andreas Fidjeland, Wayne Luk, Stephen Muggleton