@inproceedings{8b82f4690b404a2b97d650ac2d0ddb05,
title = "Improving particle approximations of the joint smoothing distribution with linear computational cost",
abstract = "Particle smoothers are widely used algorithms allowing to approximate the smoothing distribution in hidden Markov models. Existing algorithms often suffer from slow computational time or degeneracy. We propose in this paper a way to improve any of them with a linear complexity in the number of particles. When iteratively applied to the degenerated Filter-Smoother, this method leads to an algorithm which turns out to outperform all other linear particle smoothers for a fixed computational time.",
keywords = "Linear complexity, Particle smoothing, Sequential Monte-Carlo",
author = "Cyrille Dubarry and Randal Douc",
year = "2011",
month = sep,
day = "5",
doi = "10.1109/SSP.2011.5967661",
language = "English",
isbn = "9781457705700",
series = "IEEE Workshop on Statistical Signal Processing Proceedings",
pages = "209--212",
booktitle = "2011 IEEE Statistical Signal Processing Workshop, SSP 2011",
note = "2011 IEEE Statistical Signal Processing Workshop, SSP 2011 ; Conference date: 28-06-2011 Through 30-06-2011",
}