Learning is a task that generalizes many of the analyses that are applied to collections of data, and in particular, collections of sensitive individual information. Hence, it is n...
We consider the problem of determining whether a given set S in Rn is approximately convex, i.e., if there is a convex set K ∈ Rn such that the volume of their symmetric differe...
We apply and extend the priority algorithm framework introduced by Borodin, Nielsen, and Rackoff to define "greedy-like" algorithms for the (uncapacitated) facility locat...
Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching f...
In this work we study a wide range of online and offline routing and packing problems with various objectives. We provide a unified approach, based on a clean primal-dual method...