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Bayesian Inversion by ω-complete cone duality

Abstract:

The process of inverting Markov kernels relates to the important subject of Bayesian modelling and learning. In fact, Bayesian update is exactly kernel inversion. In this paper, we investigate how and when Markov kernels (aka stochastic relations, or probabilistic mappings, or simply kernels) can be inverted. We address the question both directly on the category of measurable spaces, and indirectly by interpreting kernels as Markov operators: For the direct option, we introduce a typed versio...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
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Publisher copy:
10.4230/LIPIcs.CONCUR.2016.1

Authors


Dahlqvist, F More by this author
Garnier, I More by this author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Publisher:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik Publisher's website
Volume:
59
Publication date:
2016-08-01
DOI:
ISSN:
1868-8969
Pubs id:
pubs:682583
URN:
uri:e097d26f-07f5-4bf0-9e27-c348dfe51fb9
UUID:
uuid:e097d26f-07f5-4bf0-9e27-c348dfe51fb9
Local pid:
pubs:682583
ISBN:
9783959770170

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