Projekter pr. år
Abstract
In this paper we analyse the problem of probabilistic inference in CLG networks when evidence comes in streams. In such situations, fast and scalable algorithms, able to provide accurate responses in a short time are required. We consider the instantiation of variational inference and importance sampling, two well known tools for probabilistic inference, to the CLG case. The experimental results over synthetic networks show how a parallel version importance sampling, and more precisely evidence weighting, is a promising scheme, as it is accurate and scales up with respect to available computing resources.
Originalsprog | Engelsk |
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Titel | Advances in Artificial Intelligence : 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015 Albacete, Spain, November 9–12, 2015 Proceedings |
Redaktører | José M. Puerta, José A. Gámez, Bernabe Dorronsoro, Edurne Barrenechea, Alicia Troncoso, Bruno Baruque, Mikel Galar |
Forlag | Springer |
Publikationsdato | 2015 |
Sider | 36-46 |
ISBN (Trykt) | 978-3-319-24597-3 |
ISBN (Elektronisk) | 978-3-319-24598-0 |
DOI | |
Status | Udgivet - 2015 |
Begivenhed | Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015 - Albacete, Spanien Varighed: 9 nov. 2015 → 12 nov. 2015 Konferencens nummer: 16th |
Konference
Konference | Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015 |
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Nummer | 16th |
Land/Område | Spanien |
By | Albacete |
Periode | 09/11/2015 → 12/11/2015 |
Navn | Lecture Notes in Computer Science |
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Nummer | 9422 |
ISSN | 0302-9743 |
Fingeraftryk
Dyk ned i forskningsemnerne om 'Parallel importance sampling in conditional linear Gaussian networks'. Sammen danner de et unikt fingeraftryk.Projekter
- 1 Afsluttet
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AMIDST: Analysis of MassIve Data STreams - AMIDST
Madsen, A. L., Rommerdahl Bock, A., Nielsen, T. D. & Martinez, A. M.
01/01/2014 → 31/12/2016
Projekter: Projekt › Forskning