Northwestern Events Calendar

Oct
11
2024

Statistics and Data Science Seminar: "How to Detect Out-of-Distribution Data in the Wild?"

When: Friday, October 11, 2024
11:00 AM - 12:00 PM CT

Where: Chambers Hall, Ruan Conference Room – lower level, 600 Foster St, Evanston, IL 60208 map it

Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students

Cost: free

Contact: Kisa Kowal   (847) 491-3974

Group: Department of Statistics and Data Science

Category: Academic, Lectures & Meetings

Description:

How to Detect Out-of-Distribution Data in the Wild?

Sharon Y. Li, Assistant Professor in the Department of Computer Sciences, University of Wisconsin-Madison

Abstract: When deploying machine learning models in the open and non-stationary world, their reliability is often challenged by the presence of out-of-distribution (OOD) samples. Since data shifts happen prevalently in the real world, identifying OOD inputs has become an important problem in machine learning. In this talk, I will discuss challenges, research progress, and opportunities in OOD detection. Our work is motivated by the insufficiency of existing learning objectives such as ERM --- which focuses on minimizing error only on the in-distribution (ID) data, but does not explicitly account for the uncertainty that arises outside ID data. To mitigate the fundamental limitation, I will introduce a new algorithmic framework, which jointly optimizes for both accurate classification of ID samples and reliable detection of OOD data. The learning framework integrates distributional uncertainty as a first-class construct in the learning process, thus enabling both accuracy and safety guarantees.

 

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