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» Evaluating Adaptive Problem Selection
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GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 6 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
14 years 9 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
100
Voted
ICASSP
2011
IEEE
14 years 6 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
102
Voted
CIDM
2009
IEEE
15 years 9 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...
117
Voted
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 8 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...