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ICASSP
2011
IEEE
13 years 5 days 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...
TSD
2005
Springer
14 years 1 months ago
Mapping the Speech Signal onto Electromagnetic Articulography Trajectories Using Support Vector Regression
Abstract. We report work on the mapping between the speech signal and articulatory trajectories from the MOCHA database. Contrasting previous works that used Neural Networks for th...
Asterios Toutios, Konstantinos G. Margaritis
CORR
2008
Springer
142views Education» more  CORR 2008»
13 years 8 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev
KDD
2001
ACM
145views Data Mining» more  KDD 2001»
14 years 8 months ago
Proximal support vector machine classifiers
Given a dataset, each element of which labeled by one of k labels, we construct by a very fast algorithm, a k-category proximal support vector machine (PSVM) classifier. Proximal s...
Glenn Fung, Olvi L. Mangasarian
ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 8 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich