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Learning Revenue-Maximizing Auctions With Differentiable Matching


Jun 15, 2021
Michael J. Curry, Uro Lyi, Tom Goldstein, John Dickerson


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PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning


Jun 06, 2021
Neehar Peri, Michael J. Curry, Samuel Dooley, John P. Dickerson

* First two authors contributed equally 

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


Oct 13, 2020
Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-yeh Chiang, Tom Goldstein, John P. Dickerson


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Detection as Regression: Certified Object Detection by Median Smoothing


Jul 07, 2020
Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein


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Certifying Strategyproof Auction Networks


Jun 15, 2020
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson


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Headless Horseman: Adversarial Attacks on Transfer Learning Models


Apr 20, 2020
Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu

* 5 pages, 2 figures. Accepted in ICASSP 2020. Code available on https://github.com/zhuchen03/headless-attack.git 

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


Nov 30, 2019
Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu


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