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» Learning Probabilistic Tree Grammars for Genetic Programming
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HIS
2008
13 years 8 months ago
Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining
This paper introduces a multiobjective grammar based genetic programming algorithm to solve a Web Mining problem from multiple instance perspective. This algorithm, called MOG3P-MI...
Amelia Zafra, Eva Lucrecia Gibaja Galindo, Sebasti...
EMNLP
2008
13 years 8 months ago
Sparse Multi-Scale Grammars for Discriminative Latent Variable Parsing
We present a discriminative, latent variable approach to syntactic parsing in which rules exist at multiple scales of refinement. The model is formally a latent variable CRF gramm...
Slav Petrov, Dan Klein
EUROGP
2007
Springer
135views Optimization» more  EUROGP 2007»
14 years 1 months ago
A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms
The ability of Genetic Programming to scale to problems of increasing difficulty operates on the premise that it is possible to capture regularities that exist in a problem environ...
Erik Hemberg, Conor Gilligan, Michael O'Neill, Ant...
ACL
2010
13 years 5 months ago
PCFGs, Topic Models, Adaptor Grammars and Learning Topical Collocations and the Structure of Proper Names
This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as "topic models&qu...
Mark Johnson
GECCO
2004
Springer
139views Optimization» more  GECCO 2004»
14 years 22 days ago
Chemical Genetic Programming - Coevolution Between Genotypic Strings and Phenotypic Trees
Chemical Genetic Programming (CGP) is a new method of genetic programming that introduced collision-based biochemical processes and realized dynamic mapping from genotypic strings ...
Wojciech Piaseczny, Hideaki Suzuki, Hidefumi Sawai