List of Publications (2008-2017)

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2015

Inproceedings

Luengo, David; Martino, Luca; Elvira, Victor; Bugallo, Monica

Bias correction for distributed Bayesian estimators (Inproceeding)

2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 253–256, IEEE, Cancun, 2015, ISBN: 978-1-4799-1963-5.

(Abstract | Links | BibTeX | Tags: Bayes methods, Big data, Distributed databases, Estimation, Probability density function, Wireless Sensor Networks)

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

Parallel interacting Markov adaptive importance sampling (Inproceeding)

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,

Smelly Parallel MCMC Chains (Inproceeding)

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)

2013

Journal Articles

Olmos, Pablo; Murillo-Fuentes, Juan Jose; Perez-Cruz, Fernando

Tree-Structure Expectation Propagation for LDPC Decoding Over the BEC (Journal Article)

IEEE Transactions on Information Theory, 59 (6), pp. 3354–3377, 2013, ISSN: 0018-9448.

(Abstract | Links | BibTeX | Tags: Algorithm design and analysis, Approximation algorithms, Approximation methods, BEC, belief propagation, Belief-propagation (BP), binary erasure channel, Complexity theory, decode low-density parity-check codes, Decoding, discrete memoryless channels, expectation propagation, finite-length analysis, LDPC codes, LDPC decoding, parity check codes, peeling-type algorithm, Probability density function, random graph evolution, Tanner graph, tree-structure expectation propagation)

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

Tree-Structured Expectation Propagation for LDPC Decoding over BMS Channels (Journal Article)

IEEE Transactions on Communications, 61 (10), pp. 4086–4095, 2013, ISSN: 0090-6778.

(Abstract | Links | BibTeX | Tags: Approximation algorithms, Approximation methods, BEC, belief propagation, binary erasure channel, binary memoryless symmetric channels, BMS channels, Channel Coding, Complexity theory, convolutional codes, convolutional low-density parity-check codes, Decoding, decoding block, expectation propagation, finite-length codes, LDPC decoding, message-passing algorithm, parity check codes, Probability density function, sparse linear codes, TEP algorithm, tree-structured expectation propagation, trees (mathematics), Vegetation)

Inproceedings

Koblents, Eugenia; Miguez, Joaquin

A Population Monte Carlo Scheme for Computational Inference in High Dimensional Spaces (Inproceeding)

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)

2012

Journal Articles

Maiz, Cristina; Molanes-Lopez, Elisa; Miguez, Joaquin; Djuric, Petar

A Particle Filtering Scheme for Processing Time Series Corrupted by Outliers (Journal Article)

IEEE Transactions on Signal Processing, 60 (9), pp. 4611–4627, 2012, ISSN: 1053-587X.

(Abstract | Links | BibTeX | Tags: Kalman filters, Mathematical model, nonlinear state space model, Outlier detection, prediction theory, predictive distribution, Probability density function, State-space methods, state-space models, statistical distributions, Target tracking, time serie processing, Vectors, Yttrium)

2011

Inproceedings

Balasingam, Balakumar; Bolic, Miodrag; Djuric, Petar; Miguez, Joaquin

Efficient Distributed Resampling for Particle Filters (Inproceeding)

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3772–3775, IEEE, Prague, 2011, ISSN: 1520-6149.

(Abstract | Links | BibTeX | Tags: Approximation algorithms, Copper, Covariance matrix, distributed resampling, Markov processes, Probability density function, Sequential Monte-Carlo methods, Signal processing, Signal processing algorithms)

Plata-Chaves, Jorge; Lazaro,; Artés-Rodríguez, Antonio

Optimal Neyman-Pearson Fusion in Two-Dimensional Densor Networks with Serial Architecture and Dependent Observations (Inproceeding)

Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on, pp. 1–6, Chicago, 2011, ISBN: 978-1-4577-0267-9.

(Abstract | Links | BibTeX | Tags: Bayesian methods, binary distributed detection problem, decision theory, dependent observations, Joints, local decision rule, Measurement uncertainty, Network topology, Neyman-Pearson criterion, optimal Neyman-Pearson fusion, optimum distributed detection, Parallel architectures, Performance evaluation, Probability density function, sensor dependent observations, sensor fusion, serial architecture, serial network topology, two-dimensional sensor networks, Wireless Sensor Networks)

2009

Inproceedings

Martino, Luca; Miguez, Joaquin

A Novel Rejection Sampling Scheme for Posterior Probability Distributions (Inproceeding)

2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2921–2924, IEEE, Taipei, 2009, ISSN: 1520-6149.

(Abstract | Links | BibTeX | Tags: Additive noise, arbitrary target probability distributions, Bayes methods, Bayesian methods, Monte Carlo integration, Monte Carlo methods, Monte Carlo techniques, Overbounding, posterior probability distributions, Probability density function, Probability distribution, Proposals, Rejection sampling, rejection sampling scheme, Sampling methods, Signal processing algorithms, signal sampling, Upper bound)

Martino, Luca; Miguez, Joaquin

An Adaptive Accept/Reject Sampling Algorithm for Posterior Probability Distributions (Inproceeding)

2009 IEEE/SP 15th Workshop on Statistical Signal Processing, pp. 45–48, IEEE, Cardiff, 2009, ISBN: 978-1-4244-2709-3.

(Abstract | Links | BibTeX | Tags: adaptive accept/reject sampling, Adaptive rejection sampling, arbitrary target probability distributions, Computer Simulation, Filtering, Monte Carlo integration, Monte Carlo methods, posterior probability distributions, Probability, Probability density function, Probability distribution, Proposals, Rejection sampling, Sampling methods, sensor networks, Signal processing algorithms, signal sampling, Testing)