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NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 7 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
BMCBI
2010
224views more  BMCBI 2010»
13 years 7 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
BMCBI
2010
150views more  BMCBI 2010»
13 years 7 months ago
AMS 3.0: prediction of post-translational modifications
Background: We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, us...
Subhadip Basu, Dariusz Plewczynski
AAAI
2007
13 years 9 months ago
Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution
Much of artificial intelligence research is focused on devising optimal solutions for challenging and well-defined but highly constrained problems. However, as we begin creating...
Bobby D. Bryant, Risto Miikkulainen
GECCO
2011
Springer
264views Optimization» more  GECCO 2011»
12 years 11 months ago
Critical factors in the performance of novelty search
Novelty search is a recently proposed method for evolutionary computation designed to avoid the problem of deception, in which the fitness function guides the search process away...
Steijn Kistemaker, Shimon Whiteson