We study fairness in classification, where the goal is to prevent discrimination against individuals based on their membership in some group, while maintaining utility for the classifier (the university).Expand

We describe efficient constructions of pseudo-random functions such that computing their value at any given point involves two multiple products.Expand

We propose solutions which allow a buyer to purchase digital goods from a vendor without letting the vendor learn what, and to the extent possible also when and how much, it is buying.Expand

We consider the metric uncapacitated facility location problem(UFL). In this paper we modify the (1 + 2/e)-approximation algorithm of Chudak and Shmoys to obtain a new (1.6774,1.3738)approximation… Expand

This work describes schemes for distributing between n servers the evaluation of a function which is an approximation to a random function, such that only authorized subsets of servers are able to compute the function.Expand

We give an algorithm that enables the validation of a large number of adaptively chosen hypotheses, while provably avoiding overfitting to the holdout set.Expand