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» Evaluating Adaptive Problem Selection
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GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
14 years 1 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
TCSV
2011
13 years 5 months ago
Formulating Team-Sport Video Summarization as a Resource Allocation Problem
—We propose a flexible framework to summarize team-sport videos that have been originally produced for broadcast purposes. The framework is able to integrate both the knowledge ...
Fan Chen, Christophe De Vleeschouwer
ICASSP
2011
IEEE
13 years 1 months ago
Using stacked transformations for recognizing foreign accented speech
A common problem in speech recognition for foreign accented speech is that there is not enough training data for an accent-specific or a speaker-specific recognizer. Speaker ada...
Peter Smit, Mikko Kurimo
CIDM
2009
IEEE
14 years 4 months ago
Large-scale attribute selection using wrappers
Abstract— Scheme-specific attribute selection with the wrapper and variants of forward selection is a popular attribute selection technique for classification that yields good ...
Martin Gutlein, Eibe Frank, Mark Hall, Andreas Kar...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
14 years 3 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...