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IPMU
2010
Springer
13 years 4 months ago
Attribute Value Selection Considering the Minimum Description Length Approach and Feature Granularity
Abstract. In this paper we introduce a new approach to automatic attribute and granularity selection for building optimum regression trees. The method is based on the minimum descr...
Kemal Ince, Frank Klawonn
IVC
2008
83views more  IVC 2008»
13 years 5 months ago
A minimum description length objective function for groupwise non-rigid image registration
Groupwise non-rigid registration aims to find a dense correspondence across a set of images, so that analogous structures in the images are aligned. For purely automatic inter-sub...
Stephen Marsland, Carole J. Twining, Christopher J...
CVPR
2005
IEEE
14 years 7 months ago
Optimal Sub-Shape Models by Minimum Description Length
Active shape models are a powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowle...
Georg Langs, Philipp Peloschek, Horst Bischof
JMLR
2011
192views more  JMLR 2011»
13 years 22 days ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
AI
1998
Springer
13 years 5 months ago
Uncertainty Measures of Rough Set Prediction
The main statistics used in rough set data analysis, the approximation quality, is of limited value when there is a choice of competing models for predicting a decision variable. ...
Ivo Düntsch, Günther Gediga