Parameterized Probability Monad (PPS 2016) - POPL 2016

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

Who

Adam Ścibior, Andrew D. Gordon

Track

Time Zone

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When

Sat 23 Jan 2016 15:30 - 16:30 at Room St Petersburg II - Poster Session

Abstract

We explore the use of parameterized monads for ensuring additional properties of distributions constructed by probabilistic programs. As a specific example we demonstrate how to statically ensure that conditioning in probabilistic programs does not depend on random choices made during execution. This allows us to ensure safety of application of inference algorithms such as Sequential Monte Carlo. We believe there are more potential uses of parameterized monads for probabilistic programming, such as restricting the latent space or keeping track of data types used for conditioning.

Link to Preprint

http://pps2016.soic.indiana.edu/2015/12/12/parameterized-probability-monad/

Adam Ścibior

University of Cambridge

Andrew D. Gordon

Microsoft Research and University of Edinburgh

United Kingdom

Time Zone

The program is currently displayed in (GMT-05:00) Guadalajara, Mexico City, Monterrey.

Use conference time zone: (GMT-05:00) Guadalajara, Mexico City, MonterreySelect other time zone

The GMT offsets shown reflect the offsets at the moment of the conference.

Time Band

By setting a time band, the program will dim events that are outside this time window. This is useful for (virtual) conferences with a continuous program (with repeated sessions).
The time band will also limit the events that are included in the personal iCalendar subscription service.

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Session Program

Sat 23 Jan
Displayed time zone: Guadalajara, Mexico City, Monterrey change

	15:30 - 16:30	Poster SessionPPS at Room St Petersburg II

	15:30 60m Meeting		Insomnia: Types and Modules for Probabilistic Programming PPS Aleksey Kliger Xamarin, Inc., Sean Stromsten BAE Systems, Inc. Pre-print
	15:30 60m Meeting		Finite-depth Higher-order Abstract Syntax Trees for Reasoning about Probabilistic Programs PPS Theophilos Giannakopoulos BAE Systems, Inc., Mitchell Wand Northeastern University, Andrew Cobb Northeastern University Pre-print
	15:30 60m Meeting		Coalgebraic Trace Semantics for Probabilistic Processes: Preliminary Proposal PPS Larry Moss Indiana University, Chung-chieh Shan Indiana University, Alexandra Silva Radboud University Nijmegen Pre-print
	15:30 60m Meeting		Reasoning about Probability and Nondeterminism PPS Faris Abou-Saleh University of Oxford, Kwok-Ho Cheung University of Oxford, Jeremy Gibbons University of Oxford, UK Pre-print
	15:30 60m Meeting		Fixed Points for Markov Decision Processes PPS Johannes Hölzl Technische Universität München Pre-print
	15:30 60m Meeting		A Denotational Semantics of a Probabilistic Stream-Processing Language PPS Yohei Miyamoto Graduate School of Informatics, Kyoto University, Kohei Suenaga , Koji Nakazawa Graduate School of Information Science, Nagoya University Pre-print
	15:30 60m Meeting		Observation Propagation for Importance Sampling with Likelihood Weighting PPS Ryan Culpepper Northeastern University Pre-print
	15:30 60m Meeting		Problems of the Lightweight Implementation of Probabilistic Programming PPS Oleg Kiselyov Pre-print
	15:30 60m Meeting		Parameterized Probability Monad PPS Adam Ścibior University of Cambridge, Andrew D. Gordon Microsoft Research and University of Edinburgh Pre-print
	15:30 60m Meeting		Reproducing Kernel Hilbert Space Semantics for Probabilistic Programs PPS Adam Ścibior University of Cambridge, Bernhard Schölkopf MPI Tuebingen Pre-print