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» Training a Quantum Neural Network
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ESANN
2006
15 years 5 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
132
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CIDM
2009
IEEE
15 years 10 months ago
Ensemble member selection using multi-objective optimization
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
Tuve Löfström, Ulf Johansson, Henrik Bos...
140
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ISMB
1994
15 years 5 months ago
An Improved System for Exon Recognition and Gene Modeling in Human DNA Sequence
A new version of the GRAIL system (Uberbacher and Mural, 1991; Mural et al., 1992; Uberbacher et al., 1993), called GRAILII, has recently been developed (Xu et al., 1994). GRAILII...
Yin Xu, J. Ralph Einstein, Richard J. Mural, Manes...
128
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ENGL
2007
100views more  ENGL 2007»
15 years 3 months ago
Utilizing Computational Intelligence to Assist in Software Release Decision
—Defect tracking using computational intelligence methods is used to predict software readiness in this study. By comparing predicted number of faults and number of faults discov...
Tong-Seng Quah, Mie Mie Thet Thwin
152
Voted
NN
2002
Springer
208views Neural Networks» more  NN 2002»
15 years 3 months ago
A spiking neuron model: applications and learning
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...