Jansen, N;
Kaminski, BL;
Katoen, JP;
Olmedo, F;
Gretz, F;
McIver, A;
(2015)
Conditioning in Probabilistic Programming.
In:
Electronic Notes in Theoretical Computer Science.
(pp. pp. 199-216).
Elsevier
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Abstract
In this paper, we investigate the semantic intricacies of conditioning in probabilistic programming, a major feature, e.g., in machine learning. We provide a quantitative weakest pre-condition semantics. In contrast to all other approaches, non-termination is taken into account by our semantics. We also present an operational semantics in terms of Markov models and show that expected rewards coincide with quantitative pre-conditions. A program transformation that entirely eliminates conditioning from programs is given; the correctness is shown using our semantics. Finally, we show that an inductive semantics for conditioning in non-deterministic probabilistic programs cannot exist.
| Type: | Proceedings paper |
|---|---|
| Title: | Conditioning in Probabilistic Programming |
| Event: | The 31st Conference on the Mathematical Foundations of Programming Semantics (MFPS XXXI). |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.entcs.2015.12.013 |
| Publisher version: | https://doi.org/10.1016/j.entcs.2015.12.013 |
| Language: | English |
| Additional information: | This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Probabilistic Programming, , SemanticsConditional Probabilities, Program Transformation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10094732 |
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