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

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.

Sat 23 Jan
Times are displayed in time zone: (GMT-05:00) Guadalajara, Mexico City, Monterrey change

pps-2016
16:30 - 18:00: PPS 2016 - Session 5 at Room St Petersburg II
Chair(s): Chung-chieh ShanIndiana University
pps-201616:30 - 16:50
Talk
Nathanael L. AckermanHarvard University, Cameron FreerGamalon, Daniel RoyUniversity of Toronto
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pps-201616:50 - 17:00
Meeting
pps-201617:00 - 17:20
Talk
Daniel HuangHarvard University, Greg MorrisettCornell University
Pre-print
pps-201617:20 - 17:30
Meeting
pps-201617:30 - 17:50
Talk
Friedrich GretzRWTH Aachen University, Nils JansenRWTH Aachen University, Benjamin Lucien KaminskiRWTH Aachen University, Joost-Pieter KatoenRWTH Aachen University, Federico OlmedoRWTH Aachen University
Pre-print
pps-201617:50 - 18:00
Meeting