[AI Seminar] AI Seminar sponsored by Apple -- John Dickerson (University of Maryland) -- March 20

[Adams Wei Yu]

Dear faculty and students,

We look forward to seeing you next Tuesday, March 20, at noon in *NSH 1507* for
AI Seminar sponsored by Apple. To learn more about the seminar series,
please visit the AI Seminar webpage <http://www.cs.cmu.edu/~aiseminar/>.

On Tuesday,  John Dickerson <http://jpdickerson.com/> (University of
Maryland) will give the following talk:

Title:  Diversity in Matching Markets

Abstract:

In bipartite matching problems, vertices on one side of a bipartite graph
are paired with those on the other.  In its offline variant, both sides of
the graph are known a priori; in its online variant, one side of the graph
is available offline, while vertices on the other arrive online and are
irrevocably and immediately matched (or ignored) by an algorithm.  Examples
of such problems include matching workers to firms, advertisers to
keywords, organs to patients, and riders to rideshare drivers.  Much of the
literature focuses on maximizing the total relevance---modeled via total
weight---of the matching. However, in many real-world problems, it is also
important to consider contributions of diversity: hiring a diverse pool of
candidates, displaying a relevant but diverse set of ads, and so on.

In this talk, we model the promotion of diversity in matching markets
via maximization
of a submodular function over the set of matched edges.  We present new
results in a generalization of traditional offline matching, *b*-matching,
where vertices have both lower and upper bounds on the number of adjacent
matched edges.  We also present new theoretical results in *online* submodular
bipartite matching.  Finally, we conclude with ongoing work that approaches
the problem of hiring a diverse cohort of workers through the lens of
combinatorial pure exploration (CPE) in the multiarmed bandit setting, and
discuss an ongoing experiment in this space at a large research university.

*This talk will cover joint work with Faez Ahmed, Samsara Counts, Jeff
Foster, Mark Fuge, Karthik A. Sankararaman, Candice Schumann, Aravind
Srinivasan, and Pan Xu. *


Bio:

John P Dickerson is an Assistant Professor of Computer Science at the
University of Maryland. His research centers on solving practical economic
problems using techniques from computer science, stochastic optimization,
and machine learning. He has worked extensively on theoretical and
empirical approaches to designing markets for organ allocation, dating,
admissions, and computational advertising.
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