11 citations · 50 across the 10 of their papers we have counts for
4 papers · 1 filter
ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning
Kevin Kuo, Anthony Ostuni, Elizabeth Horishny +5
The design of revenue-maximizing auctions with strong incentive guarantees is a core concern of economic theory. Computational auctions enable online advertising, sourcing, spectru…
Detection as Regression: Certified Object Detection by Median Smoothing
Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader +3
Despite the vulnerability of object detectors to adversarial attacks, very few defenses are known to date. While adversarial training can improve the empirical robustness of image…
Certifying Strategyproof Auction Networks
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein +1
Optimal auctions maximize a seller's expected revenue subject to individual rationality and strategyproofness for the buyers. Myerson's seminal work in 1981 settled the case of auc…
Headless Horseman: Adversarial Attacks on Transfer Learning Models
Ahmed Abdelkader, Michael J. Curry, Liam Fowl +5
Transfer learning facilitates the training of task-specific classifiers using pre-trained models as feature extractors. We present a family of transferable adversarial attacks agai…