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IJON
2007
91views more  IJON 2007»
15 years 1 months ago
Dynamics of parameters of neurophysiological models from phenomenological EEG modeling
We investigate a recently proposed method for the analysis of oscillatory patterns in EEG data, with respect to its capacity of further quantifying processes on slower (< 1 Hz)...
E. Olbrich, Thomas Wennekers
NIPS
2008
15 years 3 months ago
Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds
Sequential optimal design methods hold great promise for improving the efficiency of neurophysiology experiments. However, previous methods for optimal experimental design have in...
Jeremy Lewi, Robert J. Butera, David M. Schneider,...
TNN
2008
178views more  TNN 2008»
15 years 1 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
ICANN
2009
Springer
15 years 6 months ago
Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
Adrian G. Bors, Nikolaos Nasios
ESANN
2007
15 years 3 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann