Michael J. Curry

According to our database, Michael J. Curry authored at least 19 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Optimal Automated Market Makers: Differentiable Economics and Strong Duality.

Michael J. Curry, Zhou Fan, David C. Parkes

CoRR, 2024

Scalable Mechanism Design for Multi-Agent Path Finding.

Paul Friedrich, Yulun Zhang, Michael J. Curry, Ludwig Dierks, Stephen McAleer, Jiaoyang Li, Tuomas Sandholm, Sven Seuken

CoRR, 2024

Automated Design of Affine Maximizer Mechanisms in Dynamic Settings.

Michael J. Curry, Vinzenz Thoma, Darshan Chakrabarti, Stephen McAleer, Christian Kroer, Tuomas Sandholm, Niao He, Sven Seuken

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Learning Best Response Policies in Dynamic Auctions via Deep Reinforcement Learning.

Vinzenz Thoma, Michael J. Curry, Niao He, Sven Seuken

CoRR, 2023

Neural Auctions Compromise Bidder Information.

Alex Stein, Avi Schwarzschild, Michael J. Curry, Tom Goldstein, John P. Dickerson

CoRR, 2023

Differentiable Economics for Randomized Affine Maximizer Auctions.

Michael J. Curry, Tuomas Sandholm, John P. Dickerson

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Learning and Robustness With Applications To Mechanism Design.

Michael J. Curry

PhD thesis, 2022

Certified Neural Network Watermarks with Randomized Smoothing.

Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein

Proceedings of the International Conference on Machine Learning, 2022

Learning Revenue-Maximizing Auctions With Differentiable Matching.

Michael J. Curry, Uro Lyi, Tom Goldstein, John P. Dickerson

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning.

Neehar Peri, Michael J. Curry, Samuel Dooley, John Dickerson

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.

Fotini Christia, Michael J. Curry, Constantinos Daskalakis, Erik D. Demaine, John P. Dickerson, MohammadTaghi Hajiaghayi, Adam Hesterberg, Marina Knittel, Aidan Milliff

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

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

Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-yeh Chiang, Tom Goldstein, John P. Dickerson

CoRR, 2020

Detection as Regression: Certified Object Detection by Median Smoothing.

Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John P. Dickerson, Tom Goldstein

CoRR, 2020

Improving Policy-Constrained Kidney Exchange via Pre-Screening.

Duncan C. McElfresh, Michael J. Curry, Tuomas Sandholm, John Dickerson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Certifying Strategyproof Auction Networks.

Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson

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.

Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein

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.

Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

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

Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu

CoRR, 2019

Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare.

Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu

Proceedings of the Web and Internet Economics - 15th International Conference, 2019