[AI Seminar] AI Seminar sponsored by Apple -- Omer Ben-Porat

[Han Zhao]

Dear faculty and students:

We look forward to seeing you next Tuesday, Apr. 9th, at noon in *NSH 3305 *for
our AI Seminar sponsored by Apple. To learn more about the seminar series,
please visit the website <http://www.cs.cmu.edu/~aiseminar/>.
On Tuesday, Omer Ben-Porat will give the following talk:
*Title: **Regression Equilibrium*

*Abstract: *Prediction is a well-studied machine learning task, and
prediction algorithms are core ingredients in online products and services.
Despite their centrality in the competition between online companies who
offer prediction-based products, the strategic use of prediction algorithms
remains unexplored. The goal of this presentation is to examine strategic
use of prediction algorithms. We introduce a novel game-theoretic setting
that is based on the PAC learning framework, where each player (aka a
prediction algorithm aimed at competition) seeks to maximize the sum of
points for which it produces an accurate prediction and the others do not.
We show that algorithms aiming at generalization may wittingly mispredict
some points to perform better than others in expectation. We analyze the
empirical game, i.e., the game induced on a given sample, prove that it
always possesses a pure Nash equilibrium, and show that every
better-response learning process converges. Moreover, our
learning-theoretic analysis suggests that players can, with high
probability, learn an
approximate pure Nash equilibrium for the whole population using a small
number of samples.

Based on a joint work with Moshe Tennenholtz.
-- 

*Han ZhaoMachine Learning Department*


*School of Computer ScienceCarnegie Mellon UniversityMobile: +1-*
*412-652-4404*
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