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Workshop
Learning in Presence of Strategic Behavior
Omer Ben-Porat · Nika Haghtalab · Annie Liang · Yishay Mansour · David Parkes

Mon Dec 13 09:00 AM -- 02:50 PM (PST) @ None
Event URL: https://sites.google.com/view/strategicml/about »

In recent years, machine learning has been called upon to solve increasingly more complex tasks and to regulate many aspects of our social, economic, and technological world. These applications include learning economic policies from data, prediction in financial markets, learning personalize models across population of users, and ranking qualified candidates for admission, hiring, and lending. These tasks take place in a complex social and economic context where the learners and objects of learning are often people or organizations that are impacted by the learning algorithm and, in return, can take actions that influence the learning process. Learning in this context calls for a new vision for machine learning and economics that aligns the incentives and interests of the learners and other parties and is robust to the evolving social and economic needs. This workshop explores a view of machine learning and economics that considers interactions of learning systems with a wide range of social and strategic behaviors. Examples of these problems include: multi-agent learning systems, welfare-aware machine learning, learning from strategic and economic data, learning as a behavioral model, and causal inference for learning impact of strategic choices.

Mon 9:00 a.m. - 9:40 a.m.
Keynote 1: (Keynote)
Mon 9:40 a.m. - 10:20 a.m.
Keynote 2: (Keynote)
Mon 10:20 a.m. - 10:50 a.m.
Moderated Discussion (Discussion Panel)
Mon 11:10 a.m. - 11:17 a.m.
Spotlight 1: Exploration and Incentives in Reinforcement Learning (Spotlights)   
Max Simchowitz · Aleksandrs Slivkins
Mon 11:17 a.m. - 11:20 a.m.
Q&A for Spotlight 1 (Q&A)
Mon 11:20 a.m. - 11:27 a.m.
Spotlight 2: Models of fairness in federated learning (Spotlights)   
Kate Donahue · Jon Kleinberg
Mon 11:27 a.m. - 11:30 a.m.
Q&A for Spotlight 2 (Q&A)
Mon 11:30 a.m. - 11:37 a.m.
Spotlight 3: Efficient Competitions and Online Learning with Strategic Forecasters (Spotlights)   
Anish Thilagar · Rafael Frongillo · Bo Waggoner · Robert Gomez
Mon 11:37 a.m. - 11:40 a.m.
Q&A for Spotlight 3 (Q&A)
Mon 11:40 a.m. - 11:47 a.m.
Spotlight 4: Estimation of Standard Asymmetric Auction Models (Spotlights)   
Yeshwanth Cherapanamjeri · Constantinos Daskalakis · Andrew Ilyas · Emmanouil Zampetakis
Mon 11:47 a.m. - 11:50 a.m.
Q&A for Spotlight 4 (Q&A)
Mon 11:50 a.m. - 11:57 a.m.
Spotlight 5: Strategic clustering (Spotlights)   
Ana-Andreea Stoica · Christos Papadimitriou
Mon 11:57 a.m. - 12:00 p.m.
Q&A for Spotlight 5 (Q&A)
Mon 12:00 p.m. - 1:00 p.m.
Poster Session
Mon 1:00 p.m. - 1:40 a.m.
Keynote 3: (Keynote)
Mon 1:40 p.m. - 2:20 p.m.
Keynote 4: (Keynote)
Mon 2:20 p.m. - 2:50 p.m.
Moderated Discussion (Discussion Panel)

Author Information

Omer Ben-Porat (Tel-Aviv University)
Nika Haghtalab (University of California, Berkeley)
Annie Liang (UPenn)
Yishay Mansour (Tel Aviv University / Google)
David Parkes (Harvard University)

David C. Parkes is Gordon McKay Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University. He was the recipient of the NSF Career Award, the Alfred P. Sloan Fellowship, the Thouron Scholarship and the Harvard University Roslyn Abramson Award for Teaching. Parkes received his Ph.D. degree in Computer and Information Science from the University of Pennsylvania in 2001, and an M.Eng. (First class) in Engineering and Computing Science from Oxford University in 1995. At Harvard, Parkes leads the EconCS group and teaches classes in artificial intelligence, optimization, and topics at the intersection between computer science and economics. Parkes has served as Program Chair of ACM EC’07 and AAMAS’08 and General Chair of ACM EC’10, served on the editorial board of Journal of Artificial Intelligence Research, and currently serves as Editor of Games and Economic Behavior and on the boards of Journal of Autonomous Agents and Multi-agent Systems and INFORMS Journal of Computing. His research interests include computational mechanism design, electronic commerce, stochastic optimization, preference elicitation, market design, bounded rationality, computational social choice, networks and incentives, multi-agent systems, crowd-sourcing and social computing.

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