381 citations · 1.4k across the 100 of their papers we have counts for
4 papers · 1 filter
Jointly Private Convex Programming
Justin Hsu, Zhiyi Huang, Aaron Roth +1
In this paper we present an extremely general method for approximately solving a large family of convex programs where the solution can be divided between different agents, subject…
Privacy and Truthful Equilibrium Selection for Aggregative Games
Rachel Cummings, Michael Kearns, Aaron Roth +1
We study a very general class of games --- multi-dimensional aggregative games --- which in particular generalize both anonymous games and weighted congestion games. For any such g…
Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)
Sampath Kannan, Jamie Morgenstern, Aaron Roth +1
We present a mechanism for computing asymptotically stable school optimal matchings, while guaranteeing that it is an asymptotic dominant strategy for every student to report their…
Dual Query: Practical Private Query Release for High Dimensional Data
Marco Gaboardi, Emilio Jesús Gallego Arias, Justin Hsu +2
We present a practical, differentially private algorithm for answering a large number of queries on high dimensional datasets. Like all algorithms for this task, ours necessarily h…