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» Choosing Multiple Parameters for Support Vector Machines
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ICASSP
2011
IEEE
14 years 1 months ago
Deep neural networks for acoustic emotion recognition: Raising the benchmarks
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
André Stuhlsatz, Christine Meyer, Florian E...
BMCBI
2006
146views more  BMCBI 2006»
14 years 10 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
QRE
2008
140views more  QRE 2008»
14 years 9 months ago
Discrete mixtures of kernels for Kriging-based optimization
: Kriging-based exploration strategies often rely on a single Ordinary Kriging model which parametric covariance kernel is selected a priori or on the basis of an initial data set....
David Ginsbourger, Céline Helbert, Laurent ...
EMSOFT
2006
Springer
15 years 1 months ago
Multi-level software reconfiguration for sensor networks
In-situ reconfiguration of software is indispensable in embedded networked sensing systems. It is required for re-tasking a deployed network, fixing bugs, introducing new features...
Rahul Balani, Chih-Chieh Han, Ram Kumar Rengaswamy...
FGR
2002
IEEE
229views Biometrics» more  FGR 2002»
15 years 2 months ago
An Approach to Automatic Recognition of Spontaneous Facial Actions
We present ongoing work on a project for automatic recognition of spontaneous facial actions. Spontaneous facial expressions differ substantially from posed expressions, similar t...
Bjorn Braathen, Marian Stewart Bartlett, Gwen Litt...