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» Learning the Common Structure of Data
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156
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CORR
2006
Springer
153views Education» more  CORR 2006»
15 years 3 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
107
Voted
EMNLP
2007
15 years 4 months ago
Structural Correspondence Learning for Dependency Parsing
Following (Blitzer et al., 2006), we present an application of structural correspondence learning to non-projective dependency parsing (McDonald et al., 2005). To induce the corre...
Nobuyuki Shimizu, Hiroshi Nakagawa
142
Voted
GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
15 years 8 months ago
Bayesian network structure learning using cooperative coevolution
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
Olivier Barrière, Evelyne Lutton, Pierre-He...
164
Voted
CVPR
2011
IEEE
14 years 10 months ago
Learning structured prediction models for interactive image labeling
We propose structured models for image labeling that take into account the dependencies among the image labels explicitly. These models are more expressive than independent label ...
Thomas Mensink, Jakob Verbeek, Gabriela Csurka
ECCV
2008
Springer
16 years 5 months ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert