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ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
15 years 3 months ago
Blind separation of statistically independent signals with mixed sub-Gaussian and super-Gaussian probability distributions
— In the context of Independent Component Analysis (ICA), we propose a simple method for online estimation of activation functions in order to blindly separate instantaneous mixt...
Muhammad Tufail, Masahide Abe, Masayuki Kawamata
CIARP
2006
Springer
14 years 11 months ago
Robustness Analysis of the Neural Gas Learning Algorithm
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
Carolina Saavedra, Sebastián Moreno, Rodrig...
NIPS
2008
14 years 11 months ago
Bayesian Kernel Shaping for Learning Control
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...
80
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SIAMSC
2008
237views more  SIAMSC 2008»
14 years 9 months ago
A Variational Shape Optimization Approach for Image Segmentation with a Mumford--Shah Functional
We introduce a novel computational method for a Mumford-Shah functional, which decomposes a given image into smooth regions separated by closed curves. Casting this as a shape opti...
Günay Dogan, Pedro Morin, Ricardo H. Nochetto
TNN
2010
234views Management» more  TNN 2010»
14 years 4 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes