Spring 2022

Learning in the Presence of Strategic Behavior

Monday, Mar 28, 2022 to Friday, Apr 1, 2022 

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Georgios Piliouras (Singapore University of Technology and Design; chair), Fei Fang (Carnegie Mellon University), Nika Haghtalab (UC Berkeley), Christos Papadimitriou (Columbia University), Vasilis Syrgkanis (Microsoft Research), Éva Tardos (Cornell University)

There is an increasing practical need to understand the foundations of machine learning in the presence of incentives: (i) data ingested by machine learning algorithms are either owned or generated by self-interested parties and (ii) machine learning is deployed to optimize economic systems, like auctions, or to learn how to strategize in economic systems. This workshop will cover topics such as (1) learning with humans in the loop, (2) learning when data providers have a vested interest in the outcome of the learning process, (3) learning and dynamics as a game-theoretic solution concept, and (4) analyzing data (econometrics) from strategic interactions.

Registration is required to attend this boot camp. Space may be limited, and you are advised to register early. The link to the registration form will appear on this page approximately 10 weeks before the boot camp. Please await confirmation of your acceptance before booking your travel.

Further details about this workshop will be posted in due course. To contact the organizers about this workshop, please complete this form.

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