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NIPS
2008
14 years 11 months ago
Generative versus discriminative training of RBMs for classification of fMRI images
Neuroimaging datasets often have a very large number of voxels and a very small number of training cases, which means that overfitting of models for this data can become a very se...
Tanya Schmah, Geoffrey E. Hinton, Richard S. Zemel...
ICDM
2009
IEEE
184views Data Mining» more  ICDM 2009»
14 years 7 months ago
Improved Multi Label Classification in Hierarchical Taxonomies
Hierarchical taxonomies are used to organize and retrieve information in many domains, especially those dealing with large and rapidly growing amounts of information. In many of t...
Kunal Punera, Suju Rajan
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
15 years 4 months ago
Best SubTree genetic programming
The result of the program encoded into a Genetic Programming (GP) tree is usually returned by the root of that tree. However, this is not a general strategy. In this paper we pres...
Oana Muntean, Laura Diosan, Mihai Oltean
PKDD
2005
Springer
142views Data Mining» more  PKDD 2005»
15 years 3 months ago
Speeding Up Logistic Model Tree Induction
Logistic Model Trees have been shown to be very accurate and compact classifiers [8]. Their greatest disadvantage is the computational complexity of inducing the logistic regressi...
Marc Sumner, Eibe Frank, Mark A. Hall
GECCO
2007
Springer
166views Optimization» more  GECCO 2007»
15 years 4 months ago
Comparison of tree and graph encodings as function of problem complexity
In this paper, we analyze two general-purpose encoding types, trees and graphs systematically, focusing on trends over increasingly complex problems. Tree and graph encodings are ...
Michael D. Schmidt, Hod Lipson