2020

2020
Yiling Chen, Haifeng Xu, and Shuran Zheng. 2020. “Selling Information Through Consulting.” In ACM-SIAM Symposium on Discrete Algorithms (SODA20). Download
Ben Green and Salome Viljoen. 2020. “Algorithmic realism: expanding the boundaries of algorithmic thought.” In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* ’20), Pp. 19-31. Association for Computing Machinery. Download
Daniel J. Moroz, Daniel J. Aronoff, Neha Narula, and David C. Parkes. 2020. “Double-Spend Counterattacks: Threat of Retaliation in Proof-of-Work Systems.” CoRR abs/2002.10736 . Download
Debmalya Mandal, Goran Radanovic, and David C. Parkes. 2020. “The Effectiveness of Peer Prediction in Long-Term Forecasting.” In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2020) . Download
Ben Green. 2020. “The false promise of risk assessments: epistemic reform and the limits of fairness.” In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* ’20), Pp. 594-606. Association for Computing Machinery. Download
Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, and Yang Liu. 2020. “How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations.” Artificial Intelligence, 283, 103238 . Download
Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik, Melvin Gruesbeck, David C. Parkes, and Richard Socher. 2020. “Improving Equality and Productivity with AI-Driven Tax Policies.” CoRR abs/2004.13332 . Download
Sarah Keren, Haifeng Xu, Kofi Kwapong, David C. Parkes, and Barbara Grosz. 2020. “Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents.” In Proceedings of 34th AAAI Conference on Artificial Intelligence (AAAI-2020). Download
Nir Rosenfeld, Aron Szanto, and David C. Parkes. 2020. “A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone.” In Proceedings of the 29th World Wide Web Conference (WWW 2020), Pp. 1018-1028. Download
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
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
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
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