Zhun Deng, He Sun, Steven Wu, Linjun Zhang, and David C. Parkes. 2023. “Reinforcement Learning with Stepwise Fairness Constraints.” In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS) , Pp. 10594-10618 .

Jamelle Watson-Daniels, David C. Parkes, and Berk Ustun. 2023. “Predictive Multiplicity in Probabilistic Classification.” In Proc. of Association for the Advancement of Artificial Intelligence, Pp. 10306 - 10314. AAAI.

Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, and David C. Parkes. 2021. “Learning Representations by Humans.” In ICML 2021, Pp. 4227-4238.

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.

Haris Aziz, Hau Chan, Barton E. Lee, and David C. Parkes. 2020. “The capacity constrained facility location problem.” Games Econ. Behavior, 124:478–490, Pp. 478-490.

Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, Yang Liu, and David C. Parkes. 2020. “How do fairness definitions fare? testing public attitudes towards three algorithmic definitions of fairness in loan allocations.” Artificial Intelligence, 283, 103238.

Nir Rosenfeld, Anna Hilgard, Sai S. Ravindranath, and David C. Parkes. 2020. “From predictions to decisions: Using lookahead regularization.” In In Annual Conference on Neural Information Processing Systems, NeurIPS ’20.

Haris Aziz, Hau Chan, Barton E. Lee, and David C. Parkes. 2019. “The Capacity Constrained Facility Location Problem.” In Proceedings of the 15th Int. Conf. on Web and Internet Economics, (WINE 2019), Pp. 336.

Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David Parkes, and Yang Liu. 2019. “How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness.” In Proceedings of AI Ethics and Society (AIES), Pp. 99-106.

Christos Dimitrakakis, Yang Liu, David C. Parkes, and Goran Radanovic. 2019. “Bayesian Fairness.” In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI).

Berk Ustun, Yang Liu, and David C. Parkes. 2019. “Fairness without Harm: Decoupled Classifiers with Preference Guarantees.” In Proceedings of the 36th International Conference on Machine Learning (ICML’19), Pp. 6373-6382.

Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, and David C. Parkes. 2019. “Learning Representations by Humans, for Humans.” In NeurIPS Workshop on Human-Centric Machine Learning.

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.

David C. Parkes and Rakesh V. Vohra. 2019. Algorithmic and Economic Perspectives on Fairness.

Rediet Abebe, Jon M. Kleinberg, and David C. Parkes. 2017. “Fair Division via Social Comparison.” In Proc. 16th Conf. on Autonomous Agents and Multiagent Systems (AAMAS’17), Pp. 281-289.