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» Learning Probabilistic Tree Grammars for Genetic Programming
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GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
14 years 2 months ago
Evolving problem heuristics with on-line ACGP
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...
Cezary Z. Janikow
NIPS
2001
13 years 9 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning
IEAAIE
2010
Springer
13 years 6 months ago
Web Usage Mining for Improving Students Performance in Learning Management Systems
An innovative technique based on multi-objective grammar guided genetic programming (MOG3P-MI) is proposed to detect the most relevant activities that a student needs to pass a cou...
Amelia Zafra, Sebastián Ventura
ISCI
2006
96views more  ISCI 2006»
13 years 8 months ago
A comparison of classification accuracy of four genetic programming-evolved intelligent structures
We investigate the effectiveness of GP-generated intelligent structures in classification tasks. Specifically, we present and use four context-free grammars to describe (1) decisi...
Athanasios Tsakonas
ICML
1994
IEEE
13 years 12 months ago
Hierarchical Self-Organization in Genetic programming
This paper presents an approach to automatic discovery of functions in Genetic Programming. The approach is based on discovery of useful building blocks by analyzing the evolution...
Justinian P. Rosca, Dana H. Ballard