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ICCS
2004
Springer
15 years 3 months ago
Designing Digital Circuits for the Knapsack Problem
Abstract. Multi Expression Programming (MEP) is a Genetic Programming variant that uses linear chromosomes for solution encoding. A unique feature of MEP is its ability of encoding...
Mihai Oltean, Crina Grosan, Mihaela Oltean
GECCO
2004
Springer
115views Optimization» more  GECCO 2004»
15 years 3 months ago
Robotic Control Using Hierarchical Genetic Programming
In this paper, we compare the performance of hierarchical GP methods (Automatically Defined Functions, Module Acquisition, Adaptive Representation through Learning) with the canon...
Marcin L. Pilat, Franz Oppacher
IJCAI
2001
14 years 11 months ago
Neural Logic Network Learning using Genetic Programming
Neural Logic Network or Neulonet is a hybrid of neural network expert systems. Its strength lies in its ability to learn and to represent human logic in decision making using comp...
Chew Lim Tan, Henry Wai Kit Chia
BMCBI
2007
144views more  BMCBI 2007»
14 years 9 months ago
Motif kernel generated by genetic programming improves remote homology and fold detection
Background: Protein remote homology detection is a central problem in computational biology. Most recent methods train support vector machines to discriminate between related and ...
Tony Håndstad, Arne J. H. Hestnes, Pål...
CORR
2006
Springer
130views Education» more  CORR 2006»
14 years 9 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...