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GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
14 years 1 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
14 years 8 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
IJCV
2008
192views more  IJCV 2008»
13 years 7 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
BMCBI
2007
98views more  BMCBI 2007»
13 years 7 months ago
Duration learning for analysis of nanopore ionic current blockades
Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications ...
Alexander G. Churbanov, Carl Baribault, Stephen Wi...
BMCBI
2010
176views more  BMCBI 2010»
13 years 7 months ago
TargetSpy: a supervised machine learning approach for microRNA target prediction
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...