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Coffee and Check-In
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Opening Remarks
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Min-Max Optimization (Part I)
Constantinos Daskalakis (MIT)
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Break
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Min-Max Optimization (Part II)
Constantinos Daskalakis (MIT)
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Lunch
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Learning as a Solution Concept (Part I)
Éva Tardos (Cornell University)
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Break
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Learning as a Solution Concept (Part II)
Éva Tardos (Cornell University)
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Reception
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Min-Max Optimization (Part III)
Constantinos Daskalakis (MIT)
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Break
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Min-Max Optimization (Part IV)
Constantinos Daskalakis (MIT)
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Lunch
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Dynamical Systems and Learning in Games (Part I)
Georgios Piliouras (Singapore University of Technology and Design)
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Break
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Dynamical Systems and Learning in Games (Part II)
Georgios Piliouras (Singapore University of Technology and Design)
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Dynamical Systems and Learning in Games (Part III)
Georgios Piliouras (Singapore University of Technology and Design)
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Break
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Dynamical Systems and Learning in Games (Part IV)
Georgios Piliouras (Singapore University of Technology and Design)
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Lunch
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Learning and Incentives (Part I)
Nika Haghtalab (UC Berkeley)
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Break
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Learning and Incentives (Part II)
Nika Haghtalab (UC Berkeley)
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Econometrics in Games and Auctions (Part I)
Vasilis Syrgkanis (Microsoft Research)
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Break
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Econometrics in Games and Auctions (Part II)
Vasilis Syrgkanis (Microsoft Research)
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Lunch
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Learning and Incentives (Part III)
Nika Haghtalab (UC Berkeley)
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Break
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Learning and Incentives (Part IV)
Nika Haghtalab (UC Berkeley)
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Town Hall for Program Participants
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Reinforcement Learning (Part I)
Dylan Foster (Microsoft Research)
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Break
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Reinforcement Learning (Part II)
Dylan Foster (Microsoft Research)
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Lunch
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Multi-Agent Reinforcement Learning (Part I)
Chi Jin (Princeton University)
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Break
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Multi-Agent Reinforcement Learning (Part II)
Chi Jin (Princeton University)