AIC Seminar Series
First-Order Probabilistic Inference
|Rodrigo de Salvo Braz||University of California Berkeley||[Home Page]|
Notice: hosted by David Israel
Date: Tuesday July 29, 2008 at 16:00
Location: EJ228 (SRI E building) (Directions)
Many Artificial Intelligence (AI) tasks, such as natural language
processing, commonsense reasoning and vision, could be naturally
modeled by a language and associated inference engine using both
relational (first-order) predicates and probabilistic information.
While logic has been the basis for much AI development and is a
powerful framework for using relational predicates, its lack of
representation for probabilistic knowledge severely limits its
application to many tasks. Graphical models and Machine Learning, on
the other hand, can capture much of probabilistic reasoning but lack
convenient means for using relational predicates.
In the last fifteen years, many frameworks have been proposed for
merging those two approaches but have mainly been probabilistic logic
languages resorting to propositionalization of relational predicates
(and, as a consequence, ordinary graphical models inference). This has
the severe disadvantage of ignoring the relational structure of the
model and potentially causing exponential blowups in inference time.
I will talk about my work in integrating logic and probabilistic
inference in a more seamless way. This includes Lifted First-Order
Probabilistic Inference, a way of performing inference directly on
first-order representation, without propositionalization, and work on
DBLOG (Dynamic Bayesian Logic), an extension of BLOG (Bayesian Logic,
by Milch and Russell) for temporal models such as data association and
activity recognition. I will conclude with what I see as important
future directions in this field.
Bio for Rodrigo de Salvo Braz||
Rodrigo de Salvo Braz was born in São Paulo, Brazil. He graduated from
Universidade de São Paulo in 1993 with a B.Sc. in Computer Science. He
also obtained a M.Sc. degree in Computer Science from the same
department in 1998, while working for companies such as Bull Systems
and PC Magazine Brazil. He spent two years as a graduate student at
the Department of Cognitive and Linguistic Sciences at Brown
University from 1998 to 2000. During his study in the Computer Science
department at the University of Illinois, he focused his research on
First-Order Probabilistic Inference and Natural Language Processing.
He has been a Postdoctoral Researcher at the Computer Science Division
of EECS at University of California, Berkeley since August 2007, under
the supervision of Prof. Stuart Russell.