David C. Parkes

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 156

Top Venues

Publications

Tonghan Wang, Yanchen Jiang, David C. Parkes
GemNet: Menu-Based, Strategy-Proof Multi-Bidder Auctions Through Deep Learning. CoRR (2024)
Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. ICLR (2024)
Luca D'Amico-Wong, Gary Qiurui Ma, David C. Parkes
Strategic Recommendation: Revenue Optimal Matching for Online Platforms (Student Abstract). AAAI (2024)
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal Auctions through Deep Learning: Advances in Differentiable Economics. J. ACM 71 (1) (2024)
Safwan Hossain, Tonghan Wang, Tao Lin, Yiling Chen, David C. Parkes, Haifeng Xu
Multi-Sender Persuasion - A Computational Perspective. CoRR (2024)
Luca D'Amico-Wong, Hugh Zhang, Marc Lanctot, David C. Parkes
Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization. CoRR (2024)
Luca D'Amico-Wong, Yannai A. Gonczarowski, Gary Qiurui Ma, David C. Parkes
Disrupting Bipartite Trading Networks: Matching for Revenue Maximization. CoRR (2024)
Dima Ivanov, Paul Dütting, Inbal Talgam-Cohen, Tonghan Wang, David C. Parkes
Principal-Agent Reinforcement Learning. CoRR (2024)
Paul Dütting, Felix A. Fischer, David C. Parkes
Nontruthful Position Auctions Are More Robust to Misspecification. Math. Oper. Res. 49 (2) (2024)
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
Generative Adversarial Equilibrium Solvers. ICLR (2024)
Michael J. Curry, Zhou Fan, David C. Parkes
Optimal Automated Market Makers: Differentiable Economics and Strong Duality. CoRR (2024)
Sai Srivatsa Ravindranath, Zhe Feng, Di Wang, Manzil Zaheer, Aranyak Mehta, David C. Parkes
Deep Reinforcement Learning for Sequential Combinatorial Auctions. CoRR (2024)
Jamelle Watson-Daniels, Flávio du Pin Calmon, Alexander D'Amour, Carol Xuan Long, David C. Parkes, Berk Ustun
Predictive Churn with the Set of Good Models. CoRR (2024)
Edwin Zhang, Sadie Zhao, Tonghan Wang, Safwan Hossain, Henry Gasztowtt, Stephan Zheng, David C. Parkes, Milind Tambe, Yiling Chen
Social Environment Design. CoRR (2024)
Xintong Wang, Gary Qiurui Ma, Alon Eden, Clara Li, Alexander Trott, Stephan Zheng, David C. Parkes
Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study. WWW (2023)
Zhou Fan, Francisco J. Marmolejo Cossío, Daniel J. Moroz, Michael Neuder, Rithvik Rao, David C. Parkes
Strategic Liquidity Provision in Uniswap V3. AFT (2023)
He Sun, Zhun Deng, Hui Chen, David C. Parkes
Decision-Aware Conditional GANs for Time Series Data. ICAIF (2023)
Matthias Gerstgrasser, David C. Parkes
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning. ICML (2023)
Matheus Venturyne Xavier Ferreira, David C. Parkes
Credible Decentralized Exchange Design via Verifiable Sequencing Rules. STOC (2023)
Alon Eden, Gary Qiurui Ma, David C. Parkes
Platform Equilibrium: Analayzing Social Welfare in Online Market Places. CoRR (2023)
Manuel Wuthrich, Mark York, David C. Parkes
Eliciting Information from participants with Competing Incentives and Dependent Beliefs. CoRR (2023)
Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes
Reinforcement Learning with Stepwise Fairness Constraints. AISTATS (2023)
Sai Srivatsa Ravindranath, Yanchen Jiang, David C. Parkes
Data Market Design through Deep Learning. CoRR (2023)
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
Generative Adversarial Equilibrium Solvers. CoRR (2023)
Sai Srivatsa Ravindranath, Yanchen Jiang, David C. Parkes
Data Market Design through Deep Learning. NeurIPS (2023)
Sara Fish, Paul Gölz, David C. Parkes, Ariel D. Procaccia, Gili Rusak, Itai Shapira, Manuel Wüthrich
Generative Social Choice. CoRR (2023)
Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
Predictive Multiplicity in Probabilistic Classification. AAAI (2023)
Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. CoRR (2023)
Tonghan Wang, Paul Duetting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes
Deep Contract Design via Discontinuous Networks. NeurIPS (2023)
Tonghan Wang, Paul Dütting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes
Deep Contract Design via Discontinuous Piecewise Affine Neural Networks. CoRR (2023)
Yaniv Yacoby, John Girash, David C. Parkes
Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health. SIGCSE (1) (2023)
Hugh Zhang, David C. Parkes
Chain-of-Thought Reasoning is a Policy Improvement Operator. CoRR (2023)
Yaniv Yacoby, John Girash, David C. Parkes
Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health. CoRR (2022)
Gianluca Brero, Nicolas Lepore, Eric Mibuari, David C. Parkes
Learning to Mitigate AI Collusion on Economic Platforms. CoRR (2022)
Mira Finkelstein, Nitsan Levy Schlot, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenschein, Sarah Keren
Explainable Reinforcement Learning via Model Transforms. NeurIPS (2022)
Matthias Gerstgrasser, David C. Parkes
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning. CoRR (2022)
Xintong Wang, Gary Qiurui Ma, Alon Eden, Clara Li, Alexander Trott, Stephan Zheng, David C. Parkes
Using Reinforcement Learning to Study Platform Economies under Market Shocks. CoRR (2022)
Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
Predictive Multiplicity in Probabilistic Classification. CoRR (2022)
Gianluca Brero, Alon Eden, Darshan Chakrabarti, Matthias Gerstgrasser, Vincent Li, David C. Parkes
Learning Stackelberg Equilibria and Applications to Economic Design Games. CoRR (2022)
Rediet Abebe, T.-H. Hubert Chan, Jon M. Kleinberg, Zhibin Liang, David C. Parkes, Mauro Sozio, Charalampos E. Tsourakakis
Opinion Dynamics Optimization by Varying Susceptibility to Persuasion via Non-Convex Local Search. ACM Trans. Knowl. Discov. Data 16 (2) (2022)
Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David C. Parkes, William H. Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence. CoRR (2022)
Matheus V. X. Ferreira, David C. Parkes
Credible Decentralized Exchange Design via Verifiable Sequencing Rules. CoRR (2022)
Hongyao Ma, Fei Fang, David C. Parkes
Spatio-Temporal Pricing for Ridesharing Platforms. Oper. Res. 70 (2) (2022)
Zhun Deng, He Sun, Zhiwei Steven Wu, Linjun Zhang, David C. Parkes
Reinforcement Learning with Stepwise Fairness Constraints. CoRR (2022)
Gianluca Brero, Eric Mibuari, Nicolas Lepore, David C. Parkes
Learning to Mitigate AI Collusion on Economic Platforms. NeurIPS (2022)
Mira Finkelstein, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenshein, Sarah Keren
Reinforcement Learning Explainability via Model Transforms (Student Abstract). AAAI (2022)
Mira Finkelstein, Lucy Liu, Nitsan Levy Schlot, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenshein, Sarah Keren
Explainable Reinforcement Learning via Model Transforms. CoRR (2022)
Matthias Gerstgrasser, Rakshit Trivedi, David C. Parkes
CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning. ICLR (2022)
Zhou Fan, Francisco J. Marmolejo Cossío, Ben Altschuler, He Sun, Xintong Wang, David C. Parkes
Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design. CoRR (2022)
Zhou Fan, Francisco J. Marmolejo Cossío, Ben Altschuler, He Sun, Xintong Wang, David C. Parkes
Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design✱. ICAIF (2022)
Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes
Learning Representations by Humans, for Humans. ICML (2021)
Stephan Zheng, Alexander Trott, Sunil Srinivasa, David C. Parkes, Richard Socher
The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning. CoRR (2021)
Mark York, Munther Dahleh, David C. Parkes
Eliciting Social Knowledge for Creditworthiness Assessment. CoRR (2021)
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern
Dynamic Posted-Price Mechanisms for the Blockchain Transaction Fee Market (Invited Talk). Tokenomics (2021)
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern
Dynamic Posted-Price Mechanisms for the Blockchain Transaction-Fee Market. CoRR (2021)
Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes
Low-cost attacks on Ethereum 2.0 by sub-1/3 stakeholders. CoRR (2021)
Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, Duncan Rheingans-Yoo
Reinforcement Learning of Sequential Price Mechanisms. AAAI (2021)
David C. Parkes
Playing with symmetry with neural networks. Nat. Mach. Intell. 3 (8) (2021)
Sai Srivatsa Ravindranath, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers, David C. Parkes
Deep Learning for Two-Sided Matching. CoRR (2021)
Paul Tylkin, Goran Radanovic, David C. Parkes
Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments. AAMAS (2021)
Vincent Conitzer, Zhe Feng, David C. Parkes, Eric Sodomka
Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss. WINE (2021)
Sarah A. Wu, Rose E. Wang, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, Max Kleiman-Weiner
Too Many Cooks: Bayesian Inference for Coordinating Multi-Agent Collaboration. Top. Cogn. Sci. 13 (2) (2021)
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal auctions through deep learning. Commun. ACM 64 (8) (2021)
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern
Dynamic posted-price mechanisms for the blockchain transaction-fee market. AFT (2021)
Michael Neuder, Rithvik Rao, Daniel J. Moroz, David C. Parkes
Strategic Liquidity Provision in Uniswap v3. CoRR (2021)
Mark York, Munther Dahleh, David C. Parkes
Eliciting Social Knowledge for Creditworthiness Assessment. WINE (2021)
Rediet Abebe, T.-H. Hubert Chan, Jon M. Kleinberg, Zhibin Liang, David C. Parkes, Mauro Sozio, Charalampos E. Tsourakakis
Opinion Dynamics with Varying Susceptibility to Persuasion via Non-Convex Local Search. CoRR (2020)
Hau Chan, David C. Parkes, Karim R. Lakhani
The Price of Anarchy of Self-Selection in Tullock Contests. AAMAS (2020)
Sarah Keren, Haifeng Xu, Kofi Kwapong, David C. Parkes, Barbara J. Grosz
Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents. AAAI (2020)
Rose E. Wang, Sarah A. Wu, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, Max Kleiman-Weiner
Too many cooks: Coordinating multi-agent collaboration through inverse planning. CoRR (2020)
Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu
How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations. Artif. Intell. 283 (2020)
Vincent Conitzer, Zhe Feng, David C. Parkes, Eric Sodomka
Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss. CoRR (2020)
Nir Rosenfeld, Aron Szanto, David C. Parkes
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. WWW (2020)
Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes
Defending Against Malicious Reorgs in Tezos Proof-of-Stake. AFT (2020)
Malvika Rao, David F. Bacon, David C. Parkes, Margo I. Seltzer
Incentivizing Deep Fixes in Software Economies. IEEE Trans. Software Eng. 46 (1) (2020)
Sarah Keren, Sara Bernardini, Kofi Kwapong, David C. Parkes
Reasoning About Plan Robustness Versus Plan Cost for Partially Informed Agents. KR (2020)
Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes
From Predictions to Decisions: Using Lookahead Regularization. CoRR (2020)
Rose E. Wang, Sarah A. Wu, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, Max Kleiman-Weiner
Too Many Cooks: Coordinating Multi-agent Collaboration Through Inverse Planning. AAMAS (2020)
Hongyao Ma, Fei Fang, David C. Parkes
Spatio-temporal pricing for ridesharing platforms. SIGecom Exch. 18 (2) (2020)
Haris Aziz, Hau Chan, Barton E. Lee, David C. Parkes
The capacity constrained facility location problem. Games Econ. Behav. 124 (2020)
Hongyao Ma, Reshef Meir, David C. Parkes, Elena Wu-Yan
Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present-Bias. AAMAS (2020)
Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik, Melvin Gruesbeck, David C. Parkes, Richard Socher
The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies. CoRR (2020)
He Sun, Zhun Deng, Hui Chen, David C. Parkes
Decision-Aware Conditional GANs for Time Series Data. CoRR (2020)
Daniel J. Moroz, Daniel J. Aronoff, Neha Narula, David C. Parkes
Double-Spend Counterattacks: Threat of Retaliation in Proof-of-Work Systems. CoRR (2020)
Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, Duncan Rheingans-Yoo
Reinforcement Learning of Simple Indirect Mechanisms. CoRR (2020)
Nir Rosenfeld, Anna Hilgard, Sai Srivatsa Ravindranath, David C. Parkes
From Predictions to Decisions: Using Lookahead Regularization. NeurIPS (2020)
Ian T. Foster, David C. Parkes, Stephan Zheng
The Rise of AI-Driven Simulators: Building a New Crystal Ball. CoRR (2020)
Nir Rosenfeld, Aron Szanto, David C. Parkes
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. CoRR (2020)
Zhe Feng, David C. Parkes, Haifeng Xu
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation. ICML (2020)
Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes
Defending Against Malicious Reorgs in Tezos Proof-of-Stake. CoRR (2020)
Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah
Peer Prediction with Heterogeneous Users. ACM Trans. Economics and Comput. 8 (1) (2020)
Sarah A. Wu, Rose E. Wang, James A. Evans, Josh Tenenbaum, David C. Parkes, Max Kleiman-Weiner
Too many cooks: Coordinating multi-agent collaboration through inverse planning. CogSci (2020)
Debmalya Mandal, Radanovic Goran, David C. Parkes
The Effectiveness of Peer Prediction in Long-Term Forecasting. AAAI (2020)
Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla
Learning to Collaborate in Markov Decision Processes. ICML (2019)
Debmalya Mandal, David C. Parkes
Weighted Tensor Completion for Time-Series Causal Inference. CoRR (2019)
Jack Serrino, Max Kleiman-Weiner, David C. Parkes, Josh Tenenbaum
Finding Friend and Foe in Multi-Agent Games. NeurIPS (2019)
Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes
Selfish Behavior in the Tezos Proof-of-Stake Protocol. CoRR (2019)
Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes
Learning Representations by Humans, for Humans. CoRR (2019)
Hongyao Ma, Fei Fang, David C. Parkes
Spatio-Temporal Pricing for Ridesharing Platforms. EC (2019)
David C. Parkes, Rakesh V. Vohra, et al.
Algorithmic and Economic Perspectives on Fairness. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

David C. Parkes