Michael J. Curry

Orcid: 0000-0001-8052-5074

Affiliations:
  • University of Zürich, Switzerland
  • Harvard University, Cambridge, MA, USA
  • University of Maryland, College Park, MD, USA (PhD)


According to our database1, Michael J. Curry authored at least 25 papers between 2019 and 2025.

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Bibliography

2025
Aligned Textual Scoring Rules.
CoRR, July, 2025

LLM-Powered Preference Elicitation in Combinatorial Assignment.
CoRR, February, 2025

2024
Truthful Aggregation of LLMs with an Application to Online Advertising.
CoRR, 2024

Optimal Automated Market Makers: Differentiable Economics and Strong Duality.
CoRR, 2024

Scalable Mechanism Design for Multi-Agent Path Finding.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Automated Design of Affine Maximizer Mechanisms in Dynamic Settings.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning Best Response Policies in Dynamic Auctions via Deep Reinforcement Learning.
CoRR, 2023

Neural Auctions Compromise Bidder Information.
CoRR, 2023

Differentiable Economics for Randomized Affine Maximizer Auctions.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Learning Solutions in Large Economic Networks using Deep Multi-Agent Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
Learning and Robustness With Applications To Mechanism Design.
PhD thesis, 2022

Finding General Equilibria in Many-Agent Economic Simulations Using Deep Reinforcement Learning.
CoRR, 2022

Certified Neural Network Watermarks with Randomized Smoothing.
Proceedings of the International Conference on Machine Learning, 2022

Learning Revenue-Maximizing Auctions With Differentiable Matching.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalable Equilibrium Computation in Multi-agent Influence Games on Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning.
CoRR, 2020

Detection as Regression: Certified Object Detection by Median Smoothing.
CoRR, 2020

Vandermonde Wave Function Ansatz for Improved Variational Monte Carlo.
Proceedings of the Fourth IEEE/ACM Workshop on Deep Learning on Supercomputers, 2020

Improving Policy-Constrained Kidney Exchange via Pre-Screening.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Certifying Strategyproof Auction Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Detection as Regression: Certified Object Detection with Median Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Headless Horseman: Adversarial Attacks on Transfer Learning Models.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Mix and Match: Markov Chains & Mixing Times for Matching in Rideshare.
CoRR, 2019

Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare.
Proceedings of the Web and Internet Economics - 15th International Conference, 2019


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