Conference Publications

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Fernandez-Bes, Jesus; Elvira, Victor; Vaerenbergh, Steven Van

A Probabilistic Least-Mean-Squares Filter Inproceedings

In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2199–2203, IEEE, Brisbane, 2015, ISBN: 978-1-4673-6997-8.

Abstract | Links | BibTeX | Tags: adaptable step size LMS algorithm, Adaptation models, adaptive filtering, Approximation algorithms, Bayesian machine learning techniques, efficient approximation algorithm, filtering theory, Least squares approximations, least-mean-squares, probabilistic least mean squares filter, Probabilistic logic, probabilisticmodels, Probability, Signal processing algorithms, Standards, state-space models


Koblents, Eugenia; Miguez, Joaquin

A Population Monte Carlo Scheme for Computational Inference in High Dimensional Spaces Inproceedings

In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 6318–6322, IEEE, Vancouver, 2013, ISSN: 1520-6149.

Abstract | Links | BibTeX | Tags: Approximation methods, computational inference, degeneracy of importance weights, high dimensional spaces, Importance sampling, importance weights, iterative importance sampling, iterative methods, mixture-PMC, mixture-PMC algorithm, Monte Carlo methods, MPMC, nonlinear transformations, population Monte Carlo, population Monte Carlo scheme, Probability density function, probability distributions, Proposals, Sociology, Standards


Garcia-Moreno, Pablo; Artés-Rodríguez, Antonio; Hansen, Lars Kai

A Hold-out Method to Correct PCA Variance Inflation Inproceedings

In: 2012 3rd International Workshop on Cognitive Information Processing (CIP), pp. 1–6, IEEE, Baiona, 2012, ISBN: 978-1-4673-1878-5.

Abstract | Links | BibTeX | Tags: Approximation methods, classification scenario, computational complexity, computational cost, Computational efficiency, correction method, hold-out method, hold-out procedure, leave-one-out procedure, LOO method, LOO procedure, Mathematical model, PCA algorithm, PCA variance inflation, Principal component analysis, singular value decomposition, Standards, SVD, Training