SPLASH 2022
Mon 5 - Sat 10 December 2022 Auckland, New Zealand
Fri 9 Dec 2022 16:30 - 17:00 at Seminar Room G007 - Probabilistic Chair(s): Benjamin Lucien Kaminski

We present a novel static analysis technique to derive higher moments for program variables for a large class of probabilistic loops with potentially uncountable state spaces. Our approach is fully automatic, meaning it does not rely on externally provided invariants or templates. We employ algebraic techniques based on linear recurrences and introduce program transformations to simplify probabilistic programs while preserving their statistical properties. We develop power reduction techniques to further simplify the polynomial arithmetic of probabilistic programs and define the theory of moment-computable probabilistic loops for which higher moments can precisely be computed. Our work has applications towards recovering probability distributions of random variables and computing tail probabilities. The empirical evaluation of our results demonstrates the applicability of our work on many challenging examples.

Fri 9 Dec

Displayed time zone: Auckland, Wellington change

15:30 - 17:00
ProbabilisticOOPSLA at Seminar Room G007
Chair(s): Benjamin Lucien Kaminski Saarland University and University College London
15:30
30m
Talk
Semi-symbolic Inference for Efficient Streaming Probabilistic Programming
OOPSLA
Eric Atkinson Massachusetts Institute of Technology, Charles Yuan Massachusetts Institute of Technology, Guillaume Baudart Inria, Louis Mandel IBM Research, Michael Carbin Massachusetts Institute of Technology
DOI
16:00
30m
Talk
Symbolic Execution for Randomized Programs
OOPSLA
Zachary Susag Cornell University, Sumit Lahiri IIT Kanpur, Justin Hsu Cornell University, Subhajit Roy IIT Kanpur
DOI
16:30
30m
Talk
This Is the Moment for Probabilistic Loops
OOPSLA
DOI