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The expectation-propagation algorithm: a tutorial - Part 1
Multi angle
Authors : Barthelmé, Simon (Author of the conference)
CIRM (Publisher )
62F15 - Bayesian inference
62J12 - Generalized linear models
CIRM (Publisher )
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Abstract :
The Expectation-Propagation algorithm was introduced by Minka in 2001, and is today still one of the most effective algorithms for approximate inference. It is relatively difficult to implement well but in certain cases it can give results that are almost exact, while being much faster than MCMC. In this course I will review EP and classical applications to Generalised Linear Models and Gaussian Process models. I will also introduce some recent developments, including applications of EP to ABC problems, and discuss how to parallelise EP effectively.
MSC Codes : 62F15 - Bayesian inference
62J12 - Generalized linear models
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Information on the Video
Film maker : Hennenfent, GuillaumeLanguage : English Available date : 16/03/16 Conference Date : 02/03/16 Subseries : Research talks arXiv category : Methodology ; Computation ; Statistics Theory Mathematical Area(s) : Probability & Statistics Format : MP4 (.mp4) - HD Video Time : 01:00:20 Targeted Audience : Researchers Download : https://videos.cirm-math.fr/2016-03-02_Barthelme.mp4 
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Information on the Event
Event Title : Thematic month on statistics - Week 5: Bayesian statistics and algorithms / Mois thématique sur les statistiques - Semaine 5 : Semaine Bayésienne et algorithmesEvent Organizers : Le Gouic, Thibaut ; Pommeret, Denys ; Willer, Thomas Dates : 29/02/16 - 04/03/16 Event Year : 2016 Event URL : http://conferences.cirm-math.fr/1619.html
Citation Data
DOI : 10.24350/CIRM.V.18937603Cite this video as: Barthelmé, Simon (2016). The expectation-propagation algorithm: a tutorial - Part 1. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.18937603 URI : http://dx.doi.org/10.24350/CIRM.V.18937603 |
See Also
- [Multi angle] Variational Bayes methods and algorithms - Part 1 / Author of the conference Keribin, Christine.
- [Multi angle] Exploring the presence of complex dependence structures in epidemiological and genomic data through flexible clustering / Author of the conference Richardson, Sylvia.
- [Multi angle] Approximate Bayesian Computation methods for model choice a machine learning point of view - Part 1 / Author of the conference Marin, Jean-Michel.
- [Post-edited] Markov Chain Monte Carlo Methods - Part 1 / Author of the conference Robert, Christian P..
Bibliography
