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When Algorithmic Game Theory Met Machine Learning
【2014.12.16 2:00pm, N204】

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 2014-12-10 

  Colloquia & Seminars 

  Speaker

Christos Papadimitriou (University of California at Berkeley)

  Title

When Algorithmic Game Theory Met Machine Learning

  Time

Dec. 16,  14:00-15:00am

  Venue

N204

  Abstract

We have seen some remarkable new points of contact between Machine Learning and Algorithmic Game Theory over the past decade.
Here I will review the ways in which learning algorithms have been adapted as solution concepts, or employed as a crucial tool in Mechanism Design, ultimately dwelling on two current work s in which Mechanism Design is used to optimize data acquisition for Statistical Learning, and Stackelberg competitions are employed to model the classification of strategic points. 

  Affiliation

Christos Papadimitriou was inducted as a Fellow of the ACM in 2001 and awarded the Knuth Prize in 2002. He became a fellow of the US National Academy of Engineering for contributions to complexity theory, database theory, and combinatorial optimization. In 2009 he was elected to the US National Academy of Sciences. In 2012, he, along with Elias Koutsoupias, was awarded the Gödel Prize for their joint work on the concept of the price of anarchy. 

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