Michael J. Curry

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 25

Top Topics

Nonparametric Regression

Candidate Matches

Automated Design

Top Venues

Publications

Michael J. Curry, Vinzenz Thoma, Darshan Chakrabarti, Stephen McAleer, Christian Kroer, Tuomas Sandholm, Niao He, Sven Seuken
Automated Design of Affine Maximizer Mechanisms in Dynamic Settings. AAAI (2024)
Michael J. Curry, Vinzenz Thoma, Darshan Chakrabarti, Stephen McAleer, Christian Kroer, Tuomas Sandholm, Niao He, Sven Seuken
Automated Design of Affine Maximizer Mechanisms in Dynamic Settings. CoRR (2024)
Ermis Soumalias, Michael J. Curry, Sven Seuken
Truthful Aggregation of LLMs with an Application to Online Advertising. CoRR (2024)
Michael J. Curry, Zhou Fan, David C. Parkes
Optimal Automated Market Makers: Differentiable Economics and Strong Duality. CoRR (2024)
Michael J. Curry, Tuomas Sandholm, John P. Dickerson
Differentiable Economics for Randomized Affine Maximizer Auctions. IJCAI (2023)
Alex Stein, Avi Schwarzschild, Michael J. Curry, Tom Goldstein, John P. Dickerson
Neural Auctions Compromise Bidder Information. CoRR (2023)
Arpit Bansal, Ping-yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
Certified Neural Network Watermarks with Randomized Smoothing. CoRR (2022)
Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
Certified Neural Network Watermarks with Randomized Smoothing. ICML (2022)
Michael J. Curry, Tuomas Sandholm, John P. Dickerson
Differentiable Economics for Randomized Affine Maximizer Auctions. CoRR (2022)
Michael J. Curry, Uro Lyi, Tom Goldstein, John P. Dickerson
Learning Revenue-Maximizing Auctions With Differentiable Matching. AISTATS (2022)
Neehar Peri, Michael J. Curry, Samuel Dooley, John P. Dickerson
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. CoRR (2021)
Michael J. Curry, Uro Lyi, Tom Goldstein, John Dickerson
Learning Revenue-Maximizing Auctions With Differentiable Matching. CoRR (2021)
Neehar Peri, Michael J. Curry, Samuel Dooley, John Dickerson
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. NeurIPS (2021)
Fotini Christia, Michael J. Curry, Constantinos Daskalakis, Erik D. Demaine, John P. Dickerson, MohammadTaghi Hajiaghayi, Adam Hesterberg, Marina Knittel, Aidan Milliff
Scalable Equilibrium Computation in Multi-agent Influence Games on Networks. AAAI (2021)
Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu
Headless Horseman: Adversarial Attacks on Transfer Learning Models. ICASSP (2020)
Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. CoRR (2020)
Duncan C. McElfresh, Michael J. Curry, Tuomas Sandholm, John Dickerson
Improving Policy-Constrained Kidney Exchange via Pre-Screening. NeurIPS (2020)
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
Certifying Strategyproof Auction Networks. CoRR (2020)
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson
Certifying Strategyproof Auction Networks. NeurIPS (2020)
Ping-Yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John P. Dickerson, Tom Goldstein
Detection as Regression: Certified Object Detection by Median Smoothing. CoRR (2020)
Duncan C. McElfresh, Michael J. Curry, Tuomas Sandholm, John P. Dickerson
Improving Policy-Constrained Kidney Exchange via Pre-Screening. CoRR (2020)
Ping-Yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein
Detection as Regression: Certified Object Detection with Median Smoothing. NeurIPS (2020)
Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu
Headless Horseman: Adversarial Attacks on Transfer Learning Models. CoRR (2020)
Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu
Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare. WINE (2019)
Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu
Mix and Match: Markov Chains & Mixing Times for Matching in Rideshare. CoRR (2019)