Date & Time:
October 28, 2022 12:00 pm – 1:30 pm
Location:
Crerar 390, 5730 S. Ellis Ave., Chicago, IL,
Register
10/28/2022 12:00 PM 10/28/2022 01:30 PM America/Chicago Stefanie Jegelka (MIT) – Understanding Generalization and Improving Invariances in Graph Representation Learning CS/Stats/Data Science Institute Distinguished Speaker Series Crerar 390, 5730 S. Ellis Ave., Chicago, IL,

Graph representation learning is a recurring task in applications such as computational chemistry, recommendation, reasoning, or learning for combinatorial optimization. Throughout, understanding the generalization, invariances and out-of-distribution robustness of graph neural networks in an important challenge.

First, we consider out-of-distribution generalization in widely used message passing graph neural networks (MPGNNs). We aim to understand conditions under which such generalization is possible. Another important consideration for defining data shifts is an appropriate metric. We show that a pseudometric combining trees and optimal transport correlates well with the stability of MPGNNs.

Second, many approaches to graph representation learning exploit spectral information. However, eigenvectors and eigenspaces demand specific model invariances to process them in a consistent way. We propose a new architecture that encodes these invariances, can be combined with MPNNs, transformers and other set architectures, and theoretically and empirically goes beyond existing models.

This talk is based on joint work with Ching-Yao Chuang, Joshua Robinson, Derek Lim, Keyulu Xu, Jingling Li, Mozhi Zhang, Simon S. Du, Ken-ichi Kawarabayashi, Lingxiao Zhao, Tess Smidt, Suvrit Sra and Haggai Maron.

This talk will also be broadcast via Zoom. Please register to receive viewing information.

Speakers

Stefanie Jegelka

X-Consortium Career Development Associate Professor in the Department of EECS at MIT.

Stefanie Jegelka is an X-Consortium Career Development Associate Professor in the Department of EECS at MIT. She is a member of the Computer Science and AI Lab (CSAIL), the Center for Statistics and an affiliate of IDSS and ORC. Before joining MIT, she was a postdoctoral researcher at UC Berkeley, and obtained her PhD from ETH Zurich and the Max Planck Institute for Intelligent Systems. Stefanie has received a Sloan Research Fellowship, an NSF CAREER Award, a DARPA Young Faculty Award, Google research awards, a Two Sigma faculty research award, the German Pattern Recognition Award and a Best Paper Award at the International Conference for Machine Learning (ICML). She has also been invited as a sectional lecturer at the ICM 2022. She has served as an Area Chair for NeurIPS and ICML, as Action Editor for JMLR and as Program Chair for ICML 2022. Her research interests span the theory and practice of algorithmic machine learning.

Agenda

Friday, October 28, 2022
12:00–12:30

Lunch & Socializing

Lunch will be provided on a first come, first serve basis.

12:30–13:30

Talk and Q&A

Registration

Register
10/28/2022 12:00 PM 10/28/2022 01:30 PM America/Chicago Stefanie Jegelka (MIT) – Understanding Generalization and Improving Invariances in Graph Representation Learning CS/Stats/Data Science Institute Distinguished Speaker Series Crerar 390, 5730 S. Ellis Ave., Chicago, IL,

Related News & Events

In the News

Data Ecology: A Socio-Technical Approach to Controlling Dataflows

Sep 18, 2024
UChicago CS News

NeurIPS 2023 Award-winning paper by DSI Faculty Bo Li, DecodingTrust, provides a comprehensive framework for assessing trustworthiness of GPT models

Feb 01, 2024
Video

“Machine Learning Foundations Accelerate Innovation and Promote Trustworthiness” by Rebecca Willett

Jan 26, 2024
Video

Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao

Jan 23, 2024
UChicago CS News

UChicago Undergrad Analyzes Machine Learning Models Used By CPD, Uncovers Lack of Transparency About Data Usage

Oct 31, 2023
In the News

In The News: U.N. Officials Urge Regulation of Artificial Intelligence

"Security Council members said they feared that a new technology might prove a major threat to world peace."
Jul 27, 2023
UChicago CS News

UChicago Computer Scientists Bring in Generative Neural Networks to Stop Real-Time Video From Lagging

Jun 29, 2023
UChicago CS News

UChicago Assistant Professor Raul Castro Fernandez Receives 2023 ACM SIGMOD Test-of-Time Award

Jun 27, 2023
Michael Franklin
UChicago CS News

Mike Franklin, Dan Nicolae Receive 2023 Arthur L. Kelly Faculty Prize

Jun 02, 2023
UChicago CS News

PhD Student Kevin Bryson Receives NSF Graduate Research Fellowship to Create Equitable Algorithmic Data Tools

Apr 14, 2023
UChicago CS News

Computer Science Displays Catch Attention at MSI’s Annual Robot Block Party

Apr 07, 2023
UChicago CS News

UChicago, Stanford Researchers Explore How Robots and Computers Can Help Strangers Have Meaningful In-Person Conversations

Mar 29, 2023
arrow-down-largearrow-left-largearrow-right-large-greyarrow-right-large-yellowarrow-right-largearrow-right-smallbutton-arrowclosedocumentfacebookfacet-arrow-down-whitefacet-arrow-downPage 1CheckedCheckedicon-apple-t5backgroundLayer 1icon-google-t5icon-office365-t5icon-outlook-t5backgroundLayer 1icon-outlookcom-t5backgroundLayer 1icon-yahoo-t5backgroundLayer 1internal-yellowinternalintranetlinkedinlinkoutpauseplaypresentationsearch-bluesearchshareslider-arrow-nextslider-arrow-prevtwittervideoyoutube