For A General Audience
Primary Audience = Computer Scientists (Survey Talks)
- Learning Near-Optimal Auctions: Statistical, Computational, and Strategic Challenges, WINE keynote (2017).
Slides
- Application-Specific Algorithm Selection, Simons Institute Open Lecture (2016).
Slides
- Outposts Between Average- and Worst-Case Analysis: A Case Study in Auction Design, Simons Institute Workshop on Uncertainty in Computation (2016).
Slides
- Beyond Worst-Case Analysis,
Part 1 and
Part 2,
Algorithms and Uncertainty Boot Camp, Simons Institute (2016).
Slides
- Near-Optimal Equilibria,
Part 1 and
Part 2,
Economics and Computation Boot Camp, Simons Institute (2015).
Slides
- Applications of Learning Theory in Algorithmic Game Theory,
COLT 2015.
Slides
-
Intractability
in Algorithmic Game Theory, Institute for Advanced
Studies (2013).
Slides
- How To Think About Algorithmic Mechanism
Design, tutorial at FOCS 2010.
Slides.
Primary Audience = Computer Scientists (Research Talks)
Primary Audience = Game Theorists and Economists
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