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» Genetic Algorithms for Dynamic Test Data Generation
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GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
15 years 8 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
FGR
2006
IEEE
134views Biometrics» more  FGR 2006»
15 years 6 months ago
Expanding Training Set for Chinese Sign Language Recognition
In Sign Language recognition, one of the problems is to collect enough training data. Almost all of the statistical methods used in Sign Language Recognition suffer from this prob...
Chunli Wang, Xilin Chen, Wen Gao
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 8 months ago
Analysis of noisy time-series signals with GA involving viral infection with tropism
In this paper we report on a study in which genetic algorithms are applied to the analysis of noisy time-series signals, which is related to the problem of analyzing the motion ch...
Yuji Sato, Yuta Yasuda, Ryuji Goto
128
Voted
IJCNN
2007
IEEE
15 years 8 months ago
Dynamic Pooling for the Combination of Forecasts generated using Multi Level Learning
— In this paper we provide experimental results and extensions to our previous theoretical findings concerning the combination of forecasts that have been diversified by three ...
Silvia Riedel, Bogdan Gabrys
118
Voted
NIPS
1997
15 years 3 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung