Wednesday, December 4, 2019
Speaker: Joost-Pieter Katoen
Venue: Kontaktraum, Gußhaustrasse 27-29, 6th floor (new EI building, Stiege I), TU Wien
Probabilistic programming is a fascinating new direction in programming.
FaceBook, Google and Microsoft, to mention a few, are investing lots of
research efforts in probabilistic programming. Nearly every programming
Prolog, C, Python, you name it, and — yes — even Excel has been
extended with features for randomness. These languages aim to make
probabilistic modeling and machine learning accessible to any
programmer, any user.
Probabilistic programs describe recipes on how to infer conclusions
about big data from a mixture of uncertain data and real-world
observations. Bayesian networks, a key model in decision making, are
simple instances of such programs. Probabilistic programs steer
autonomous robots and self-driving cars, are key to describe security
mechanisms, naturally encode randomised algorithms, and are rapidly
encroaching AI and machine learning.
In this talk, I will explain what probabilistic programming is, give a
historical perspective, describe its applications, and indicate what
formal methods can mean for probabilistic programs.