[Lisa_seminaires] Reminder: Talk Today at 2pm in AA3195.

Aaron Courville aaron.courville at gmail.com
Mer 31 Mai 12:55:15 EDT 2017


We will have a talk today at 2pm. Our speaker is Michael Chang from MIT,
working with Josh Tenenbaum.

Date / Time: Wednesday May 31st, 2pm-3pm
Location: AA3195

Title: *Learning Visual and Physical Models of the Environment*

Abstract:
An intelligent agent can leverage a model of the environment as a prior to
accelerate future learning and generalize beyond its own experience. I view
building such models as learning simulator programs that infer latent
properties and generate predictions from observation. How can the agent
learn the primitives for these programs from observation? What are the
means of combination that operate on these primitives that allow zero-shot
generalization to come naturally? In this talk, I discuss two of my recent
work that propose potential directions for tackling these questions in the
context of learning visual concepts and intuitive physics. First, I present
an algorithm for learning factorized symbolic representations from raw
visual data. I show that these representations capture latent factors of
variation that can be manipulated like a graphics code. Next, I present a
framework for learning predictive models of intuitive physics. With
two-dimensional worlds of bouncing balls, I demonstrate that this framework
generalizes to variable object count and variable scene configurations with
only spatially and temporally local computation. I conclude by describing
open research questions motivated by the results from these approaches.

Bio:
Michael Chang is a senior in Computer Science at MIT, researching in
Professor Joshua Tenenbaum's Computational Cognitive Science Group. He is
interested in building algorithms for learning compositional programs and
bridging the strengths of symbolic and neural representations. At MIT, he
has worked on unsupervised learning of symbolic visual concepts and of
physical dynamics. Michael has spent time at the University of Michigan
researching with Professor Honglak Lee. Michael will be pursuing a Ph.D. in
Computer Science at U.C. Berkeley beginning fall 2017. Links to papers and
code are here: http://mbchang.github.io.

-- 
Aaron C. Courville
Département d’Informatique et
de recherche opérationnelle
Université de Montréal
email:  Aaron.Courville at gmail.com
-------------- section suivante --------------
Une pièce jointe HTML a été nettoyée...
URL: http://webmail.iro.umontreal.ca/pipermail/lisa_seminaires/attachments/20170531/6e4b3121/attachment.html 


Plus d'informations sur la liste de diffusion Lisa_seminaires