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Machine Learning meets Economics: Using Theory, Data, and Experiments to Design Markets, UW CSE, Nov. 13
November 13, 2012 @ 3:30 pm - 5:00 pm
Machine Learning meets Economics: Using Theory, Data, and Experiments to Design Markets, UW CSE
When: Tuesday, November 13, 2012, 3:30pm
Where: Atrium, Paul G. Allen Center for Computer Science & Engineering
What: Economists often build “structural models,” where they specify a specific model of individual behavior and then use data to estimate the parameters of the model. Although such models require strong assumptions, they have the advantage that they can make principled predictions about what would happen if the environment changed in a way that has not been observed in the past. I will describe the application of these techniques to advertiser behavior in sponsored search advertising auctions, focusing on how the models can be used for marketplace design and management. I will discuss economists’ focus on causal inference in statistical models as well as the ways in which experiments can be used to estimate and test structural models. I will also make some suggestions about research directions at the intersection of economics and machine learning.
Who: Renowned economist Susan Athey is a professor of economics at the Stanford Graduate School of Business. Athey earned her Ph.D. from Stanford in 1995. She taught at MIT for six years, at Stanford for five years, and at Harvard for six years, before returning to Stanford this fall. Her current research focuses on the economics of the Internet, online advertising and media markets, auctions, and marketplace design. She advises governments and businesses on the design of auction-based markets, and has also served as a consultant to Microsoft since 2007 in the role of chief economist. Athey is the first female recipient of the John Bates Clark Medal, awarded to the American economist under the age of 40 who is judged to have made the most significant contribution to economic thought and knowledge. In 2012, she was elected to the National Academy of Sciences.
How Much: Free
How: More information online
