901 search results - page 96 / 181 » Modelling Complex Data by Learning Which Variable to Constru... |
101
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NIPS
2001
15 years 4 months ago
2001
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
NIPS
2003
15 years 4 months ago
2003
The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experiments with artificial and realworld data demonstrate that the graphs learned from...
146
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CSDA
2007
15 years 3 months ago
2007
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
146
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ICCV
2007
IEEE
16 years 5 months ago
2007
IEEE
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
123
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ECML
2005
Springer
15 years 8 months ago
2005
Springer
We propose an omnivariate decision tree architecture which contains univariate, multivariate linear or nonlinear nodes, matching the complexity of the node to the complexity of the...