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» Adaptive Global Metamodeling with Neural Networks
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PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
13 years 8 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
CEC
2008
IEEE
13 years 11 months ago
Automatic model type selection with heterogeneous evolution: An application to RF circuit block modeling
— Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a cost effe...
Dirk Gorissen, Luciano De Tommasi, Jeroen Croon, T...
HIS
2008
13 years 6 months ago
A Sequential Learning Resource Allocation Network for Image Processing Applications
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...
Stefan Wildermann, Jürgen Teich
IJCNN
2006
IEEE
13 years 11 months ago
Local Support Vector Regression for Financial Time Series Prediction
— We consider the regression problem for financial time series. Typically, financial time series are non-stationary and volatile in nature. Because of its good generalization p...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
IJPRAI
2000
135views more  IJPRAI 2000»
13 years 4 months ago
Towards Unrestricted Lip Reading
Lip reading provides useful information in speech perception and language understanding, especially when the auditory speech is degraded. However, many current automatic lip readi...
Uwe Meier, Rainer Stiefelhagen, Jie Yang, Alex Wai...