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» Learning fault-tolerance in Radial Basis Function Networks
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ICPR
2006
IEEE
14 years 8 months ago
A Minimum Sphere Covering Approach to Pattern Classification
In this paper we present a minimum sphere covering approach to pattern classification that seeks to construct a minimum number of spheres to represent the training data and formul...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
NIPS
1994
13 years 8 months ago
Boosting the Performance of RBF Networks with Dynamic Decay Adjustment
Radial Basis Function (RBF) Networks, also known as networks of locally{tuned processing units (see 6]) are well known for their ease of use. Most algorithms used to train these t...
Michael R. Berthold, Jay Diamond
ICMCS
2006
IEEE
115views Multimedia» more  ICMCS 2006»
14 years 1 months ago
On Training Neural Network Algorithms for Odor Identification for Future Multimedia Communication Systems
Future multimedia communication system can be developed to identify, transmit and provide odors besides voice and image. In this paper, an improved odor identification method is i...
Ki-Hyeon Kwon, Namyong Kim, Hyung-Gi Byun, Krishna...
ICDM
2003
IEEE
105views Data Mining» more  ICDM 2003»
14 years 20 days ago
SVM Based Models for Predicting Foreign Currency Exchange Rates
Support vector machine (SVM) has appeared as a powerful tool for forecasting forex market and demonstrated better performance over other methods, e.g., neural network or ARIMA bas...
Joarder Kamruzzaman, Ruhul A. Sarker, Iftekhar Ahm...
JMLR
2008
116views more  JMLR 2008»
13 years 7 months ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li