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» Smoothing of Chemical Analysis Data by Neural Networks
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NIPS
1998
13 years 8 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll
IJCNN
2006
IEEE
14 years 1 months ago
Nonlinear principal component analysis of noisy data
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
William W. Hsieh
ICPR
2008
IEEE
14 years 1 months ago
Intelligence computing approach for seizure detection based on intracranial electroencephalogram (IEEG)
Epilepsy is a neurological disorder which causes two million people in the United States for suffering. In this research, we proposed a seizure detection method based on intracran...
Tsu-Wang Shen, Xavier Kuo, Chung-Shan Yu
ICANN
2009
Springer
13 years 5 months ago
MINLIP: Efficient Learning of Transformation Models
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
ICIAP
1997
ACM
13 years 11 months ago
The COMPARES Project: COnnectionist Methods for Preprocessing and Analysis of REmote Sensing Data
The European Concerted Action \COMPARES" (Concerted Action on COnnectionist Methods for Preprocessing and Analysis of REmote Sensing Data) was funded within the Environment an...
Jim Austin, Giorgio Giacinto, I. Kanellopoulos, Ke...