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ICML
2005
IEEE
16 years 7 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
IJCNN
2008
IEEE
16 years 28 days ago
A comparison of fuzzy ARTMAP and Gaussian ARTMAP neural networks for incremental learning
Abstract— Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrai...
Eric Granger, Jean-François Connolly, Rober...
CORR
2006
Springer
99views Education» more  CORR 2006»
15 years 6 months ago
Logical settings for concept learning from incomplete examples in First Order Logic
We investigate here concept learning from incomplete examples. Our first purpose is to discuss to what extent logical learning settings have to be modified in order to cope with da...
Dominique Bouthinon, Henry Soldano, Véroniq...
ICIP
2007
IEEE
16 years 8 months ago
Image Denoising with Nonparametric Hidden Markov Trees
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
ICML
2007
IEEE
16 years 7 months ago
Mixtures of hierarchical topics with Pachinko allocation
The four-level pachinko allocation model (PAM) (Li & McCallum, 2006) represents correlations among topics using a DAG structure. It does not, however, represent a nested hiera...
David M. Mimno, Wei Li, Andrew McCallum