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EMMCVPR
2005
Springer
16 years 1 months ago
Learning Hierarchical Shape Models from Examples
Abstract. We present an algorithm for automatically constructing a decompositional shape model from examples. Unlike current approaches to structural model acquisition, in which on...
Alex Levinshtein, Cristian Sminchisescu, Sven J. D...
223
Voted
KDD
2005
ACM
99views Data Mining» more  KDD 2005»
16 years 1 months ago
Disease progression modeling from historical clinical databases
This paper considers the problem of modeling disease progression from historical clinical databases, with the ultimate objective of stratifying patients into groups with clearly d...
Ronald K. Pearson, Robert J. Kingan, Alan Hochberg
189
Voted
AUSAI
1999
Springer
15 years 11 months ago
Generating Rule Sets from Model Trees
Model trees—decision trees with linear models at the leaf nodes—have recently emerged as an accurate method for numeric prediction that produces understandable models. However,...
Geoffrey Holmes, Mark Hall, Eibe Frank
AI
2011
Springer
15 years 2 months ago
Learning qualitative models from numerical data
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
220
Voted
SIGGRAPH
1999
ACM
15 years 11 months ago
Voice Puppetry
We introduce a method for predicting a control signal from another related signal, and apply it to voice puppetry: Generating full facial animation from expressive information in ...
Matthew Brand