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» Genetic Algorithms for Ambiguous Labelling Problems
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EMMCVPR
1997
Springer
13 years 9 months ago
Genetic Algorithms for Ambiguous Labelling Problems
Consistent labelling problems frequently have more than one solution. Most work in the "eld has aimed at disambiguating early in the interpretation process, using only local ...
Richard Myers, Edwin R. Hancock
IDA
2005
Springer
13 years 10 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
13 years 8 months ago
An effective genetic algorithm for the minimum-label spanning tree problem
Given a connected, undirected graph G with labeled edges, the minimum-label spanning tree problem seeks a spanning tree on G to whose edges are attached the smallest possible numb...
Jeremiah Nummela, Bryant A. Julstrom
SAC
2010
ACM
12 years 11 months ago
Convex onion peeling genetic algorithm: an efficient solution to map labeling of point-feature
Map labeling of point-feature is the problem of placing text labels to corresponding point features on a map in a way that minimizes overlaps while satisfying basic rules for the ...
Wan D. Bae, Shayma Alkobaisi, Petr Vojtechovsk&yac...
AAAI
2007
13 years 7 months ago
Multi-Label Learning by Instance Differentiation
Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
Min-Ling Zhang, Zhi-Hua Zhou