Abstract. We study two-stage, finite-scenario stochastic versions of several combinatorial optimization problems, and provide nearly tight approximation algorithms for them. Our pr...
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
: This paper presents a demand-based engineering method for designing radio networks of cellularmobile communicationsystems. The proposed procedure is based on a forward-engineerin...
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...