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» Learning Probabilistic Tree Grammars for Genetic Programming
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GECCO
2004
Springer
105views Optimization» more  GECCO 2004»
14 years 22 days ago
Softening the Structural Difficulty in Genetic Programming with TAG-Based Representation and Insertion/Deletion Operators
In a series of papers [3-8], Daida et. al. highlighted the difficulties posed to Genetic Programming (GP) by the complexity of the structural search space, and attributed the probl...
Nguyen Xuan Hoai, Robert I. McKay
FBIT
2007
IEEE
14 years 1 months ago
Developmental Evaluation in Genetic Programming: A Position Paper
—Standard genetic programming genotypes are generally highly disorganized and poorly structured, with little code replication. This is also true of existing developmental genetic...
Tuan Hao Hoang, Robert I. McKay, Daryl Essam, Nguy...
ETAI
2000
84views more  ETAI 2000»
13 years 7 months ago
Learning Stochastic Logic Programs
Stochastic logic programs combine ideas from probabilistic grammars with the expressive power of definite clause logic; as such they can be considered as an extension of probabili...
Stephen Muggleton
LREC
2010
216views Education» more  LREC 2010»
13 years 8 months ago
Automatic Grammar Rule Extraction and Ranking for Definitions
Learning texts contain much implicit knowledge which is ideally presented to the learner in a structured manner - a typical example being definitions of terms in the text, which w...
Claudia Borg, Mike Rosner, Gordon J. Pace
ACL
2009
13 years 5 months ago
Unsupervised Multilingual Grammar Induction
We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language ...
Benjamin Snyder, Tahira Naseem, Regina Barzilay