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SUMMARY:From Couplings to Probabilistic Relational Program Logics
DTSTART:20180608T101500
DTEND:20180608T110000
DTSTAMP:20260407T110838Z
UID:f45969a24b35c7d04584dc75eb8f54d2dd5c817d6cfe25dedab67383
CATEGORIES:Conferences - Seminars
DESCRIPTION:By Justin Hsu\n\nAbstract\nMany program properties are relatio
 nal\, comparing the behavior of a program (or even two different programs)
  on two different inputs. While researchers have developed various techniq
 ues for verifying such properties for standard\, deterministic programs\, 
 relational properties for probabilistic programs have been more challengin
 g. In this talk\, I will survey recent developments targeting a range of p
 robabilistic relational properties\, with motivations from privacy\, crypt
 ography\, machine learning. The key idea is to meld relational program log
 ics with an idea from probability theory\, called a probabilistic coupling
 . The logics allow a highly compositional and surprisingly general style o
 f analysis\, supporting clean proofs for a variety of probabilistic relati
 onal properties.\n\nBio\nJustin Hsu is a post-doctoral researcher at the C
 ornell University. He obtained his graduate degree from the University of 
 Pennsylvania. His research interests span formal verification and theoreti
 cal computer science\, including verification of randomized algorithms\, d
 ifferential privacy\, and game theory.\n\nMore information
LOCATION:BC 410 https://plan.epfl.ch/?room==BC%20410
STATUS:CONFIRMED
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