Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, and Andrea Tacchetti. Working Paper. “Generative Adversarial Equilibrium Solvers.” CoRR abs/2302.06607 (2023) .

Omer Nahum, Gali Noti, David C. Parkes, and Nir Rosenfeld. Working Paper. “Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces.” CoRR abs/2306.10606 (2023).

Sai Srivatsa Ravindranath, Zhe Feng, Shira Li, Jonathan Ma, Scott D. Kominers, and David C. Parkes. Working Paper. “Deep Learning for Two-Sided Matching.” CoRR abs/2107.03427 (2021).

Tonghan Wang, Paul Duetting, Dmitry Ivanov, Inbal Talgam-Cohen, and David C. Parkes. 2023. “Deep Contract Design via Discontinuous Networks.” In Proceedings of the NeurIPS 2023 (Thirty-seventh Conference on Neural Information Processing Systems).

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.

Zhe Feng, David C. Parkes, and Sai Srivatsa Ravindranath. 2022. “Machine Learning for Matching Markets.” In Online matching theory and market design. N. Immorlica, F. Echenique, and V. Vazirani (eds), Cambridge University Press.

Gianluca Brero, Darshan Chakrabarti, Alon Eden, Matthias Gerstgrasser, Vincent Li, and David C. Parkes. 2021. “Learning Stackelberg Equilibria in Sequential Price Mechanisms.” In . Proc. ICML Workshop for Reinforcement Learning Theory.

Paul Tylkin, Goran Radanovic, and David C. Parkes. 2021. “Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments.” In Proc. 20th Int. Conf. on Auton. Agents and Multiagent Systems (AAMAS), Pp. 1686-1688 .

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

Paul Duetting, Zhe Feng, Hari Narasimhan, David C. Parkes, and Sai Srivatsa Ravindranath. 2021. “Optimal auctions through deep learning.” Communications of the ACM, 64, 8, Pp. 109-116.

Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, and Duncan Rheingans-Yoo. 2021. “Reinforcement Learning of Simple Indirect Mechanisms.” In The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Pp. 5219-5227.

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.

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.

Paul Tylkin, Goran Radanovic, and David C. Parkes. 2020. “Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments.” In NeurIPS 2020 workshop on Cooperative AI.