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GECCO
2003
Springer
126views Optimization» more  GECCO 2003»
16 years 24 days ago
Coevolution and Linear Genetic Programming for Visual Learning
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
Krzysztof Krawiec, Bir Bhanu
ESANN
2006
15 years 9 months ago
Synthesis of maximum margin and multiview learning using unlabeled data
In this presentation we show the semi-supervised learning with two input sources can be transformed into a maximum margin problem to be similar to a binary SVM. Our formulation exp...
Sándor Szedmák, John Shawe-Taylor
ESANN
2001
15 years 9 months ago
Learning fault-tolerance in Radial Basis Function Networks
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
Xavier Parra, Andreu Català
IJON
2008
133views more  IJON 2008»
15 years 6 months ago
A multi-objective approach to RBF network learning
The problem of inductive supervised learning is discussed in this paper within the context of multi-objective (MOBJ) optimization. The smoothness-based apparent (effective) comple...
Illya Kokshenev, Antônio de Pádua Bra...
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
15 years 8 months ago
Subheuristic search and scalability in a hyperheuristic
Our previous work has introduced a hyperheuristic (HH) approach based on Genetic Programming (GP). There, GP employs usergiven languages where domain-specific local heuristics ar...
Robert E. Keller, Riccardo Poli