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ALT
2008
Springer
14 years 3 months ago
Numberings Optimal for Learning
This paper extends previous studies on learnability in non-acceptable numberings by considering the question: for which criteria which numberings are optimal, that is, for which nu...
Sanjay Jain, Frank Stephan
GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
13 years 10 months ago
Coordination number prediction using learning classifier systems: performance and interpretability
Jaume Bacardit, Michael Stout, Natalio Krasnogor, ...
MLDM
2005
Springer
13 years 11 months ago
A Grouping Method for Categorical Attributes Having Very Large Number of Values
In supervised machine learning, the partitioning of the values (also called grouping) of a categorical attribute aims at constructing a new synthetic attribute which keeps the info...
Marc Boullé
CVPR
2010
IEEE
14 years 2 months ago
Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
MLDM
2007
Springer
14 years 12 days ago
Kernel MDL to Determine the Number of Clusters
In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particu...
Ivan O. Kyrgyzov, Olexiy O. Kyrgyzov, Henri Ma&ici...