[Theory] 3/10 Talks at TTIC: Aditi Raghunathan, Stanford University

[Mary Marre]

*When:*      Wednesday, March 10th at* 11:10 am CT*



*Where:*     Zoom Virtual Talk (*register in advance here
<https://uchicagogroup.zoom.us/webinar/register/WN_sQlwfNDJRB2lp8s1ARxV9w>*)



*Who: *       Aditi Raghunathan, Stanford University



*Title:* Rethinking the Role of Data in Robust Machine Learning

*Abstract:* 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. In
particular, I will focus on the role of data and demonstrate the need to
question common assumptions when improving robustness to (i) adversarial
examples and (ii) spurious correlations. On the one hand, I will describe
how and why naively using more data can surprisingly hurt performance in
these settings. On the other hand, I will show that unlabeled data, when
harnessed in the right fashion, is extremely beneficial and achieves
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.

*Bio:* 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.



*Host:* *David McAllester* <mcallester 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>*
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