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2020

Romero-Medrano, Lorena; Moreno-Muñoz, P; Artés-Rodríguez, Antonio

Multinomial Sampling for hierarchical Change-Point Detection Inproceedings

In: 2020 IEEE International Workshop on Machine Learning for Signal Processing, 2020.

BibTeX | Tags: Bayesian inference, change-point detection (CPD), latent variable models, multinomial likelihoods

2018

Martino, Luca; Elvira, Victor; Miguez, Joaquín; Artés-Rodríguez, Antonio; Djuric, Petar M

A Comparison Of Clipping Strategies For Importance Sampling Inproceedings

In: 2018 IEEE Statistical Signal Processing Workshop (SSP), 2018.

Links | BibTeX | Tags: Bayesian inference, Importance sampling, Monte Carlo methods, Parameter estimation, Variance Reduction methods

2016

Martino, Luca; Elvira, Victor; Luengo, David; Corander, Jukka; Louzada, Francisco

Orthogonal Parallel MCMC Methods for Sampling and Optimization Journal Article

In: Digital Signal Processing, 58 , pp. 64–84, 2016, ISSN: 10512004.

Abstract | Links | BibTeX | Tags: Bayesian inference, Block Independent Metropolis, Journal, Optimization, Parallel Markov Chain Monte Carlo, Parallel Multiple Try Metropolis, Parallel Simulated Annealing, Recycling samples

Nazábal, Alfredo; Garcia-Moreno, Pablo; Artés-Rodríguez, Antonio; Ghahramani, Zoubin

Human Activity Recognition by Combining a Small Number of Classifiers. Journal Article

In: IEEE journal of biomedical and health informatics, 20 (5), pp. 1342 – 1351, 2016, ISSN: 2168-2208.

Abstract | Links | BibTeX | Tags: Bayes methods, Bayesian inference, Biological system modeling, Classifier combination, Databases, Estimation, Hidden Markov models, Journal, Sensor systems

Koblents, Eugenia; Míguez, Joaquín; Rodríguez, Marco A; Schmidt, Alexandra M

A Nonlinear Population Monte Carlo Scheme for the Bayesian Estimation of Parameters of α-stable Distributions Journal Article

In: Computational Statistics & Data Analysis, 95 , pp. 57–74, 2016, ISSN: 01679473.

Abstract | Links | BibTeX | Tags: Animal movement, Bayesian inference, Importance sampling, L{é}vy process, α-stable distributions

Nazabal, Alfredo; Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Ghahramani, Zoubin

Human Activity Recognition by Combining a Small Number of Classifiers Journal Article

In: IEEE journal of biomedical and health informatics, To appear , 2016, ISSN: 2168-2208.

Abstract | Links | BibTeX | Tags: Bayes methods, Bayesian inference, Biological system modeling, Classifier combination, Databases, Estimation, Hidden Markov models, Sensor systems

2015

Martino, Luca; Elvira, Victor; Luengo, David; Corander, Jukka

Parallel interacting Markov adaptive importance sampling Inproceedings

In: 2015 23rd European Signal Processing Conference (EUSIPCO), pp. 499–503, IEEE, Nice, 2015, ISBN: 978-0-9928-6263-3.

Abstract | Links | BibTeX | Tags: Adaptive importance sampling, Bayesian inference, MCMC methods, Monte Carlo methods, Parallel Chains, Probability density function, Proposals, Signal processing, Signal processing algorithms, Sociology

Martino, Luca; Elvira, Victor; Luengo, David; Artés-Rodríguez, Antonio; Corander, Jukka

Smelly Parallel MCMC Chains Inproceedings

In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4070–4074, IEEE, Brisbane, 2015, ISBN: 978-1-4673-6997-8.

Abstract | Links | BibTeX | Tags: Bayesian inference, learning (artificial intelligence), Machine learning, Markov chain Monte Carlo, Markov chain Monte Carlo algorithms, Markov processes, MC methods, MCMC algorithms, MCMC scheme, mean square error, mean square error methods, Monte Carlo methods, optimisation, parallel and interacting chains, Probability density function, Proposals, robustness, Sampling methods, Signal processing, Signal processing algorithms, signal sampling, smelly parallel chains, smelly parallel MCMC chains, Stochastic optimization

2014

Impedovo, Sebastiano; Liu, Cheng-Lin; Impedovo, Donato; Pirlo, Giuseppe; Read, Jesse; Martino, Luca; Luengo, David

Efficient Monte Carlo Methods for Multi-Dimensional Learning with Classifier Chains Journal Article

In: Pattern Recognition, 47 (3), pp. 1535–1546, 2014.

Abstract | Links | BibTeX | Tags: Bayesian inference, Classifier chains, Monte Carlo methods, Multi-dimensional classification, Multi-label classification

Martino, Luca; Elvira, Víctor; Luengo, David; Artés-Rodríguez, Antonio; Corander, Jukka

Orthogonal MCMC Algorithms Inproceedings

In: 2014 IEEE Workshop on Statistical Signal Processing (SSP 2014), Gold Coast, 2014.

Abstract | Links | BibTeX | Tags: Bayesian inference, Markov Chain Monte Carlo (MCMC), Parallel Chains, population Monte Carlo

2013

Read, Jesse; Martino, Luca; Luengo, David

Eficient Monte Carlo Optimization for Multi-Label Classifier Chains Inproceedings

In: ICASSP 2013: The 38th International Conference on Acoustics, Speech, and Signal Processing, Vancouver, 2013.

Abstract | BibTeX | Tags: Bayesian inference, Classifier chains, Monte Carlo methods, Multi-dimensional classification, Multi-label classification

2012

Salamanca, Luis; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando

Bayesian Equalization for LDPC Channel Decoding Journal Article

In: IEEE Transactions on Signal Processing, 60 (5), pp. 2672–2676, 2012, ISSN: 1053-587X.

Abstract | Links | BibTeX | Tags: Approximation methods, Bayes methods, Bayesian equalization, Bayesian estimation problem, Bayesian inference, Bayesian methods, BCJR (Bahl–Cocke–Jelinek–Raviv) algorithm, BCJR algorithm, Channel Coding, channel decoding, channel equalization, channel equalization problem, Channel estimation, channel state information, CSI, Decoding, equalisers, Equalizers, expectation propagation, expectation propagation algorithm, fading channels, graphical model representation, intersymbol interference, Kullback-Leibler divergence, LDPC, LDPC coding, low-density parity-check decoder, Modulation, parity check codes, symbol posterior estimates, Training