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» Learning with Mixtures of Trees
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IJON
2008
101views more  IJON 2008»
13 years 9 months ago
Learning dynamics and robustness of vector quantization and neural gas
Various alternatives have been developed to improve the Winner-Takes-All (WTA) mechanism in vector quantization, including the Neural Gas (NG). However, the behavior of these algo...
Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbar...
NN
2010
Springer
225views Neural Networks» more  NN 2010»
13 years 8 months ago
Learning to imitate stochastic time series in a compositional way by chaos
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Jun Namikawa, Jun Tani
JMLR
2010
154views more  JMLR 2010»
13 years 4 months ago
Infinite Predictor Subspace Models for Multitask Learning
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
Piyush Rai, Hal Daumé III
ICML
2004
IEEE
14 years 10 months ago
Parameter space exploration with Gaussian process trees
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are ...
Robert B. Gramacy, Herbert K. H. Lee, William G. M...
SAC
2006
ACM
14 years 3 months ago
Exploiting partial decision trees for feature subset selection in e-mail categorization
In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
Helmut Berger, Dieter Merkl, Michael Dittenbach