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ECCV
2010
Springer
15 years 2 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
BMCBI
2008
160views more  BMCBI 2008»
15 years 2 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...
GPEM
2008
98views more  GPEM 2008»
15 years 2 months ago
Sporadic model building for efficiency enhancement of the hierarchical BOA
Efficiency enhancement techniques--such as parallelization and hybridization--are among the most important ingredients of practical applications of genetic and evolutionary algori...
Martin Pelikan, Kumara Sastry, David E. Goldberg
BMCBI
2006
138views more  BMCBI 2006»
15 years 2 months ago
Approximation properties of haplotype tagging
Background: Single nucleotide polymorphisms (SNPs) are locations at which the genomic sequences of population members differ. Since these differences are known to follow patterns,...
Staal A. Vinterbo, Stephan Dreiseitl, Lucila Ohno-...
CPHYSICS
2006
119views more  CPHYSICS 2006»
15 years 2 months ago
GDF: A tool for function estimation through grammatical evolution
This article introduces a tool for data fitting that is based on genetic programming and especially on the grammatical evolution technique. The user needs to input a series of poi...
Ioannis G. Tsoulos, Dimitris Gavrilis, Evangelos D...