CS Colloquia: Mechanism Design, Machine Learning, and Pricing Problems

Title: Mechanism Design, Machine Learning, and Pricing ProblemsSpeaker: Maria-Florina Balcan(CMU)ABSTRACT:
In this work, we make an explicit connection between machine learning and
mechanism design. In doing so, we obtain a unified approach for considering a
variety of profit maximizing mechanism design problems, including many that
have been previously considered in the literature. In particular, we use
techniques from sample complexity in machine learning theory to reduce
problems of incentive compatible mechanism design to standard algorithmic
questions. We apply these results to a wide variety of revenue-maximizing
pricing problems, including the problem of auctioning a digital good, the
attribute auction problem, and the problem of item pricing in unlimited supply
combinatorial auctions. From a learning perspective, these settings present
several unique challenges: the loss function is discontinuous and asymmetric,
and the range of bidders' valuations may be large. This talk is based on joint work with Avrim Blum, Jason Hartline, and Yishay
Mansour.BIO:
Maria-Florina Balcan is a Ph.D. candidate at Carnegie Mellon University under
the supervision of Avrim Blum. She received B.S. and M.S. degrees from the
Faculty of Mathematics, University of Bucharest, Romania. Her main research
interests are Computational and Statistical Machine Learning, Computational
Aspects in Economics and Game Theory, and Algorithms. She is a recipient of
the IBM PhD Fellowship.

Location: Seaver Science Library (SSL) - 150

Audiences: Everyone Is Invited

Contact: CS Colloquia