Working Paper
Stephan Zheng, Alexander Trott, Sunil Srinivasa, Richard Socher, and David C. Parkes. Working Paper. “The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning.” CoRR abs/2004.13332.
Barton E. Lee, Daniel J. Moroz, and David C. Parkes. Working Paper. “An Analysis of Blockchain Governance via Political Economics”.
Ignacio Palacios-Huerta, David C. Parkes, and Richard Steinberg. Working Paper. “Combinatorial Auctions in Practice”. SSRN
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.
Daniel J. Moroz, Daniel J. Aronoff, Neha Narula, and David C. Parkes. Working Paper. “Double-Spend Counterattacks: Threat of Retaliation in Proof-of-Work Systems.” CoRR abs/2002.10736.
Michael Neuder, Daniel J. Moroz, Rithvik Rao, and David C. Parkes. Working Paper. “Low-cost attacks on Ethereum 2.0 by sub-1/3 stakeholders.” CoRR abs/2102.02247.
Hongyao Ma, Reshef Meir, David C. Parkes, and Elena Wu-Yan. Working Paper. “Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present Bias”. arXiv
Michael Neuder, Rithvik Rao, Daniel J. Moroz, and David C. Parkes. Working Paper. “Strategic Liquidity Provision in Uniswap v3”. arXiv
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.
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 .
David Parkes. 2021. “Playing with symmetry with neural networks.” Nature Machine Intelligence .
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, and Mitchell Stern. 2021. “Dynamic posted-price mechanisms for the blockchain transaction-fee market.” In AFT 2021, Pp. 86-99.
Mark York, Munther Dahleh, and David C. Parkes. 2021. “Eliciting Social Knowledge for Creditworthiness Assessment.” In Proc. 17th Conference on Web and Internet Economics .
David C. Parkes and Francesca Dominici. 2021. “Introducing the Interim Co-Editors-in-Chief.” PubPub.
Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, and David C. Parkes. 2021. “Learning Representations by Humans.” In ICML 2021, Pp. 4227-4238.
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.
Rediet Abebe, Hubert Chan, Jon Kleinberg, Zhibin Liang, David C. Parkes, Mauro Sozio, and Charalampos Tsourakakis. 2021. “Opinion Dynamics with Varying Susceptibility to Persuasion via Non-Convex Local.” ACM Transactions on Knowledge Discovery from Data, 16, Pp. 1-34.
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).
Hongyao Ma, Fei Fang, and David C. Parkes. 2021. “Spatio-temporal pricing for ridesharing platforms.” Operations Research .