Nonuniform graph partitioning with unrelated weights

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Abstract

We give a bi-criteria approximation algorithm for the Minimum Nonuniform Partitioning problem, recently introduced by Krauthgamer, Naor, Schwartz and Talwar (2014). In this problem, we are given a graph G = (V,E) on n vertices and k numbers ρ1,..., ρk. The goal is to partition the graph into k disjoint sets P1,..., Pk satisfying |Pi| ≤ ρin so as to minimize the number of edges cut by the partition. Our algorithm has an approximation ratio of O(√log n log k)for general graphs, and an O(1) approximation for graphs with excluded minors. This is an improvement upon the O(logn) algorithm of Krauthgamer, Naor, Schwartz and Talwar (2014). Our approximation ratio matches the best known ratio for the Minimum (Uniform) k-Partitioning problem. We extend our results to the case of "unrelated weights" and to the case of "unrelated d-dimensional weights". In the former case, different vertices may have different weights and the weight of a vertex may depend on the set Pi the vertex is assigned to. In the latter case, each vertex u has a d-dimensional weight r(u,i) = (r1(u,i),..., rd (u,i)) if u is assigned to Pi. Each set Pi has a d-dimensional capacity c(i) = (c1(i),..., cd (i)). The goal is to find a partition such that ∑u∈Pi r(u, i) ≤ c(i) coordinate-wise. © 2014 Springer-Verlag.

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APA

Makarychev, K., & Makarychev, Y. (2014). Nonuniform graph partitioning with unrelated weights. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8572 LNCS, pp. 812–822). Springer Verlag. https://doi.org/10.1007/978-3-662-43948-7_67

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