Publications

2020
Rupert Freeman, David M. Pennock, Chara Podimata, and Jennifer Wortman Vaughan. 2020. “No-Regret and Incentive-Compatible Online Learning.” In Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML2020). Download
Paul Duetting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, and Sai S. Ravindranath. 2020. “Optimal auctions through deep learning.” Communications of the ACM, 63, 12. Download
Arpit Agarwal, Debmalya Mandal, David C. Parkes, and Nisarg Shah. 2020. “Peer Prediction with Heterogeneous Users.” ACM Transactions on Economics and Computation, 8, 1, Pp. 2:1-2:34 . Download
Hongyao Ma, Reshef Meir, David C. Parkes, and Elena Wu-Yan. 2020. “Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present-Bias.” In , Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), Pp. 807-815. Download
Ben Berger, Alon Eden, and Michal Feldman. 2020. “On the Power and Limits of Dynamic Pricing in Combinatorial Markets.” In The 16th Conference on Web and Internet Economics, WINE'20. Download
Nir Rosenfeld, Kojin Oshiba, and Yaron Singer. 2020. “Predicting Choice with Set-Dependent Aggregation.” In Proceedings of the 37th International Conference on Machine Learning (ICML'20). Download
Hau Chan, David C. Parkes, and Karim R. Lakhani. 2020. “The Price of Anarchy of Self-Selection in Tullock Contests (Extended Abstract).” In , Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), Pp. 1795-1797. Download
Sarah Keren, Sara Bernardini, Kofi Kwapong, and David C. Parkes. 2020. “Reasoning about plan robustness versus plan cost for partially informed agents.” In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020, Pp. 550–559. Download
Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, and Duncan Rheingans-Yoo. 2020. “Reinforcement learning of simple indirect mechanisms.” In NeurIPS’20 Workshop on Machine learning for Economic Policy. Download
Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, and Duncan Rheingans-Yoo. 2020. “Reinforcement learning of simple indirect mechanisms.” In . NeurIPS’20 Workshop on Machine learning for Economic Policy. Download brero_neurips20.pdf
Yiling Chen, Haifeng Xu, and Shuran Zheng. 2020. “Selling Information Through Consulting.” In ACM-SIAM Symposium on Discrete Algorithms (SODA20). Download
Yang Liu, Juntao Wang, and Yiling Chen. 2020. “Surrogate Scoring Rules.” In Proceedings of the Twenty-first ACM Conference on Economics and Computation. (EC '20). Download
Rose E. Wang, Sarah A. Wu, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, and Max Kleiman-Weiner. 2020. “Too Many Cooks: Coordinating Multi-agent Collaboration Through Inverse Planning (Extended Abstract).” In Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), Pp. 2032-2034. Download
Yiling Chen, Yiheng Shen, and Shuran Zheng. 2020. “Truthful Data Acquisition via Peer Prediction.” In Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020). Download
2019
Ben Green. 4/2019. The Smart Enough City, Putting Technology in It's Place to Reclaim Our Urban Future., Pp. 240. Cambridge: MIT Press. Download
Ben Green and Yiling Chen. 1/2019. “Disparate Interactions: An Algorithm-in-the-Loop Analysis of Fairness in Risk Assessments.” In Conference on Fairness, Accountability, and Transparency (FAT* ’19). Download
Hongyao Ma, Fei Fang, and David C. Parkes. 2019. “Spatio-Temporal Pricing for Ridesharing Platforms.” In Proceedings of the 20th ACM Conference on Economics and Computation (EC'19), Pp. 583. Download
Berk Ustun, Alexander Spanghler, and Yang Liu. 2019. “Actionable Recourse in Linear Classification.” In ACM Conference on Fairness, Accountability, and Transparency (FAT '19). Download
David C. Parkes and Rakesh V. Vohra. 2019. Algorithmic and Economic Perspectives on Fairness. Download
Gregory D. Hager, Ann W. Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C. Parkes, Jason Schultz, Suchi Saria, Stephen F. Smith, and Milind Tambe. 2019. Artificial Intelligence for Social Good. Download

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