[Colloquium] 3/4 Talks at TTIC: Raymond Yeh, UIUC

[Mary Marre]

*When:*      Thursday, March 4th at* 11:10 am CT*



*Where:*     Zoom Virtual Talk (*register in advance here
<https://uchicagogroup.zoom.us/webinar/register/WN_byoLTO4SRAyopvO2kKizHQ>*)



*Who: *       Raymond Yeh, UIUC


*Title:   *     Extracting Structures from Data: The Black-Box, the Manual
and the Discovered

*Abstract:* Representing structure in data is at the heart of computer
vision and machine learning, i.e., the act of converting raw data into a
useful mathematical form. In this talk, I will discuss solutions that are
broadly characterized into three themes: the black-box, the manual, and the
discovered. First, I will discuss how to use deep generative models to
learn structures for face images and its application to image inpainting.
Going beyond black-box models, I will explain how to manually impose
structures in deep-nets for human pose-regression. Specifically, I will
introduce chirality nets, a family of deep-nets that respects left/right
symmetry of human poses. Lastly, I will illustrate how to discover pairwise
word-to-object structures in the context of textual-grounding and discuss
current efforts towards discovering general structures.

*Bio:* Raymond A. Yeh is a PhD candidate at the University of Illinois at
Urbana-Champaign (UIUC) advised by Alexander Schwing, Minh Do, and Mark
Hasegawa-Johnson. Previously, he has spent time interning at Google AI and
Johns Hopkins University. He is a recipient of the Google PhD Fellowship,
the Mavis Future Faculty Fellowship and the Henry Ford II Scholarship. His
research interests lie at the intersection of machine learning and computer
vision.

*Host:* Greg Shakhnarovich <greg at ttic.edu>



Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 517*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.cs.uchicago.edu/pipermail/colloquium/attachments/20210225/58833d7f/attachment-0001.html>