This work establishes a relation between this collection of network design problems and a variant of the facility location problem introduced by Karger and Minkoff, and provides optimal and approximate algorithms for several variants of this problem, depending on whether the traffic matrix is required to be symmetric.Expand

The first primal–dual algorithms for these problems are given and achieve the best known approximation guarantees and the results were not combinatorial—they were obtained by solving an exponential size linear rogramming relaxation.Expand

This paper shows that a simple clustering algorithm works without assuming any generative (probabilistic) model, and proves some new results for generative models - e.g., it can cluster all but a small fraction of points only assuming a bound on the variance.Expand

MCG is used to obtain the first constant factor approximation algorithms for the following problems: (i) multiple depot k-traveling repairmen problem with covering constraints and (ii) orienteering problem with time windows when the number of time windows is a constant.Expand

Novel algorithms for provisioning VPNs in the hose model are developed and it is shown that the VPN trees constructed by the proposed algorithms dramatically reduce bandwidth requirements compared to scenarios in which Steiner trees are employed to connect VPN endpoints.Expand

A general dual-fitting technique for analyzing online scheduling algorithms in the unrelated machines setting where the objective function involves weighted flow-time, and it is proposed that one can often analyze such algorithms by looking at the dual of the linear program for the corresponding scheduling problem, and finding a feasible dual solution as the on-line algorithm proceeds.Expand

This paper introduces an optimal low polynomial-time algorithm for one-dimensional wavelet thresholding, based on a new Dynamic-Programming (DP) formulation, and can be employed to minimize the maximum relative or absolute error in the data reconstruction.Expand

A simple and easy-to-analyze randomized approximation algorithms for several well-studied NP-hard network design problems and a simple constant-factor approximation algorithm for the single-sink buy-at-bulk network design problem.Expand

We present the first linear time (1 + /spl epsiv/)-approximation algorithm for the k-means problem for fixed k and /spl epsiv/. Our algorithm runs in O(nd) time, which is linear in the size of the… Expand

This work defines and studies the class of inference problems, in which it seeks to reconstruct a partially specified time labeling of a network in a manner consistent with an observed history of information flow, and provides results on two types of problems for temporal networks.Expand