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UAI
2004
13 years 10 months ago
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Omid Madani, Daniel J. Lizotte, Russell Greiner
CORR
2011
Springer
200views Education» more  CORR 2011»
13 years 3 months ago
Using Feature Weights to Improve Performance of Neural Networks
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant fe...
Ridwan Al Iqbal
KCAP
2009
ACM
14 years 1 months ago
An entropy inspired measure for evaluating ontology modularization
Ontology modularization has received growing interest from the research community lately, since it supports tasks such as ontology design/reuse and knowledge selection and integra...
Paul Doran, Valentina A. M. Tamma, Terry R. Payne,...
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
14 years 7 days ago
Smart crossover operator with multiple parents for a Pittsburgh learning classifier system
This paper proposes a new smart crossover operator for a Pittsburgh Learning Classifier System. This operator, unlike other recent LCS approaches of smart recombination, does not ...
Jaume Bacardit, Natalio Krasnogor
ILP
2004
Springer
14 years 1 months ago
Learning an Approximation to Inductive Logic Programming Clause Evaluation
One challenge faced by many Inductive Logic Programming (ILP) systems is poor scalability to problems with large search spaces and many examples. Randomized search methods such as ...
Frank DiMaio, Jude W. Shavlik