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ICML
2006
IEEE
16 years 7 months ago
How boosting the margin can also boost classifier complexity
Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
Lev Reyzin, Robert E. Schapire
ICML
2002
IEEE
16 years 7 months ago
Exact model averaging with naive Bayesian classifiers
The naive classifier is a well-established mathematical model whose simplicity, speed and accuracy have made it a popular choice for classification in AI and engineering. In this ...
Denver Dash, Gregory F. Cooper
ICML
2000
IEEE
16 years 7 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
ISBI
2004
IEEE
16 years 7 months ago
Modelling Noise-Induced Fibre-Orientation Error in Diffusion-Tensor MRI
Diffusion-Tensor MRI can be used to measure fibre orientation within the brain. Several studies have proposed methods to reconstruct known white matter fibre tracts in the brain. ...
Philip A. Cook, Daniel C. Alexander, Geoffrey J. M...
ISBI
2004
IEEE
16 years 7 months ago
Grid-Enabled Automatic Construction of A Two-Chamber Cardiac PDM from a Large Database of Dynamic 3D Shapes
Point Distribution Modelling (PDM) is an efficient generative technique that can be used to incorporate statistical shape priors into image analysis methods like Active Shape Mode...
Alejandro F. Frangi, Loic Boisrobert, Marcos Lauce...
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