[Colloq] REMINDER Talk -TODAY, Jan. 10 - Brian Milch, MIT

[Rachel Kalweit]

College of Computer and Information Science Colloquium

Presents:
Brian Milch
MIT

Who will speak on:
“Probabilistic Models with Unknown Objects”

Wednesday, January 10, 2007
12:00 pm
366 West Village H
Northeastern University

Abstract:
Many AI problems, from tracking aircraft based on radar blips to
extracting facts about people and events from text documents, involve
making inferences about the real-world objects that underlie some data.
In many cases, we do not know the number of underlying objects or the
mapping between objects and observations. This talk will present a
probabilistic modeling language, called Bayesian logic (or BLOG), which
allows us to represent such scenarios in a natural way. A well-formed
BLOG model fully defines a probability distribution over model
structures of a first-order logical language; these "possible worlds"
can contain varying numbers of objects with varying relations among
them. I will also describe a Markov chain Monte Carlo algorithm for
performing inference on BLOG models. This algorithm is novel in that it
does a random walk not over fully specified possible worlds, but over
partial world descriptions that instantiate only the relevant variables.
I will present the results of applying this algorithm to identify the
distinct publications referred to by a set of citation strings extracted
from online papers.
The recent paper First-Order Probabilistic Languages: Into the Unknown
gives a survey of first-order probabilistic languages.

Biography
Brian Milch is a postdoctoral researcher in the Computer Science and
Artificial Intelligence Laboratory at MIT. He received his B.S. with
honors in Symbolic Systems from Stanford University, where he worked
with Prof. Daphne Koller. He then spent a year as a research engineer at
Google before entering the computer science Ph.D. program at U.C.
Berkeley. His thesis research, with Prof. Stuart Russell, was on
representation and inference for models that combine probability and
first-order logic. He received his Ph.D. in December 2006. He is also
the recipient of an NSF Graduate Research Fellowship and a Siebel
Scholarship.


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