Mon 24 Jun 2019 15:00 - 15:20 at 224AB - Probabilistic Programming Chair(s): Martin Hirzel

We present \textsc{ISymb} an incremental
symbolic inference framework
for probabilistic programs in situations when
some loop-manipulated array data, upon
which their probabilistic models are conditioned,
undergoes small changes. To tackle the path
explosion challenge, \textsc{ISymb} is intra-procedurally
path-sensitive except
that it conducts a ``meet-over-all-paths''
analysis within an iteration of a loop
(conditioned on some observed array data).
By recomputing only the
probability distributions for the
paths affected, \textsc{ISymb} avoids
expensive symbolic inference from scratch while
also being
precision-preserving. Our evaluation with a set of
existing benchmarks shows that
\textsc{ISymb} can lead to orders of magnitude
performance improvements compared to its
non-incremental counterpart (under small changes in
observed array data).

Mon 24 Jun

pldi-2019-papers
14:00 - 15:30: PLDI Research Papers - Probabilistic Programming at 224AB
Chair(s): Martin HirzelIBM Research
pldi-2019-papers14:00 - 14:20
Talk
Steffen SmolkaCornell University, Praveen KumarCornell University, David M. KahnCarnegie Mellon University, USA, Nate FosterCornell University, Justin HsuUniversity of Wisconsin-Madison, USA, Dexter KozenCornell University, Alexandra SilvaUniversity College London
DOI Pre-print Media Attached
pldi-2019-papers14:20 - 14:40
Talk
Peixin WangShanghai Jiao Tong University, Hongfei FuIST Austria, Amir Kafshdar GoharshadyIST Austria, Krishnendu ChatterjeeIST Austria, Xudong QinEast China Normal University, China, Wenjun ShiEast China Normal University, China
Media Attached
pldi-2019-papers14:40 - 15:00
Talk
Marco Cusumano-TownerMIT-CSAIL, Feras SaadMassachusetts Institute of Technology, Alexander K. LewMassachusetts Institute of Technology, USA, Vikash MansingkhaMIT
Media Attached
pldi-2019-papers15:00 - 15:20
Talk
Jieyuan ZhangUNSW, Australia, Jingling XueUNSW Sydney
Media Attached