Date & Time:
April 5, 2021 3:00 pm – 4:00 pm
Live Stream
04/05/2021 03:00 PM 04/05/2021 04:00 PM America/Chicago Aditi Raghunathan (Stanford) – Rethinking the Role of Data in Robust Machine Learning Live Stream

Rethinking the Role of Data in Robust Machine Learning

Watch via live stream

Despite notable successes on several carefully controlled benchmarks, current machine learning (ML) systems are remarkably brittle, raising serious concerns about their deployment in safety-critical applications like self-driving cars and predictive healthcare. In this talk, I discuss fundamental obstacles to building robust ML systems and develop principled approaches that form the foundations of robust ML. I will focus on two settings where standard ML models degrade substantially: adversarial attacks on test inputs, and presence of spurious correlations like image backgrounds. I will demonstrate the need to question common assumptions in ML, particularly about the role of training data. On the one hand, I will describe how and why naively using more data can surprisingly hurt performance in these robustness settings. On the other hand, I will show that unlabeled data, when harnessed in the right fashion, is extremely beneficial and enables state-of-the-art robustness. In closing, I will discuss how to build on the foundations of robust ML and achieve wide-ranging robustness in various domains including natural language processing and vision.

Host: Ben Zhao

Aditi Raghunathan

PhD Student, Stanford University

Aditi Raghunathan is a fifth year PhD student at Stanford University advised by Percy Liang. She is interested in building robust machine learning systems with guarantees for trustworthy real-world deployment. Her research in robustness has been recognized by a Google PhD Fellowship in Machine Learning and the Open Philanthropy AI Fellowship. Among other honors, she is also the recipient of the Anita Borg Memorial Scholarship and the Stanford School of Engineering Fellowship. 

Related News & Events


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

Jan 26, 2024

Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao

Jan 23, 2024
UChicago CS News

Five UChicago CS students named to Siebel Scholars Class of 2024

Oct 02, 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 Team Wins The NIH Long COVID Computational Challenge

Jun 28, 2023
UChicago CS News

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

Jun 27, 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
UChicago CS News

Postdoc Alum John Paparrizos Named ICDE Rising Star

Mar 15, 2023
UChicago CS News

New EAGER Grant to Asst. Prof. Eric Jonas Will Explore ML for Quantum Spectrometry

Mar 03, 2023
UChicago CS News

Asst. Prof. Rana Hanocka Receives NSF Grant to Develop New AI-Driven 3D Modeling Tools

Feb 28, 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