[Pl-seminar] Reminder: 4/10 Seminar: John Tristan: Compilation of Simple Probabilistic Programs to Gibbs Sampling

[Daniel Patterson]

Reminder: this is next week!

Daniel Patterson <dbp at ccs.neu.edu> writes:

> NUPRL Seminar Presents
>
> John Tristan
> Oracle Labs
>
> 11:45AM
> Tuesday, April 10th, 2018
> Room 366 WVH (http://www.ccs.neu.edu/home/wand/directions.html)
>
> Compilation of Simple Probabilistic Programs to Gibbs Sampling.
>
> Abstract
>
> One of the several interesting challenges of probabilistic programming
> is that of compiling probabilistic programs to inference algorithms. One
> of these inference algorithms, Gibbs sampling, is particularly relevant
> because it is often statistically efficient, but unfortunately, it is
> difficult to derive and therefore compile to.
>
> In this talk, after a brief explanation of probabilistic programming and
> why its relevance to data science, I will explain some of the ideas
> behind the design of a compiler from (very) simple probabilistic
> programs to Gibbs sampling. I will also attempt to explain what it would
> mean for such a compiler to be correct.
>
> Bio
>
> Jean-Baptiste Tristan is a researcher in the machine learning group at
> Oracle Labs. He holds a Ph.D. in Computer Science from the French
> Institute for Research in Computer Science and Automation (INRIA) and a
> M.Sc. in Computer Science from the Ecole Normale Superieure of Paris.