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Theory Seminar: Dr. Shaddin Dughmi, "A Combinatorial Lens on Supervised Learning."

Event Type
Seminar/Symposium
Sponsor
Theory and Algorithms Research Area
Location
3401 Siebel Center
Date
Dec 8, 2025   10:00 - 11:00 am  
Speaker
Dr. Shaddin Dughmi
Contact
Allison Mette
E-Mail
agk@illinois.edu
Originating Calendar
Siebel School Speakers Calendar

Abstract: I will describe some recent joint results on the theory of supervised learning which follow from connections to combinatorial optimization. First, I will examine whether there are "simple" algorithmic templates that are guaranteed to include near-optimal learners in settings with large or high dimensional label spaces. This will involve understanding various recipes for regularization, and whether one such recipe is universal for supervised learning. Second, I will show that in idealized semi-supervised settings, where the unlabeled data distribution is known or can be fully learned, the forms of regularization needed for learning become much simpler. Third, I will show that the difficulty of a supervised learning problem can be captured by its finite neighborhoods.

Key to all these results is a transductive view of learning which is highly combinatorial, and closely related to bipartite matching on infinite graphs. Our proofs leverage tools from matching theory and generalize them appropriately to derive insights into learning.

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