An Application of Computable Distributions to the Semantics of Probabilistic Programs (PPS 2016)

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Wed 20 - Sat 23 January 2016 St. Petersburg, Florida, United States

Who

Daniel Huang, Greg Morrisett

Track

PPS 2016

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When

Sat 23 Jan 2016 17:00 - 17:20 at Room St Petersburg II - Session 5 Chair(s): Chung-chieh Shan

Abstract

Our attempt to give semantics to a core, functional probabilistic programming language uses computable distributions. The semantics uses largely standard techniques from denotational semantics. One nice property of computable distributions is that they are completely characterized by a sampling algorithm. Hence, it is possible to faithfully implement (in a Turing-complete language) a semantics based on computable distributions as a sampling library. We are interested in the pros and cons of using computable distributions as opposed to measure theory in giving semantics to probabilistic programming languages.

Link to Preprint

http://pps2016.soic.indiana.edu/2015/12/13/an-application-of-computable-distributions-to-the-semantics-of-probabilistic-programs/

Daniel Huang

Harvard University

Greg Morrisett

Cornell University