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» Choosing Multiple Parameters for Support Vector Machines
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ICASSP
2011
IEEE
12 years 11 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»
13 years 8 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»
13 years 7 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
13 years 11 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»
14 years 27 days 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...