We investigate the unbalanced cut problems. A cut (A, B) is called unbalanced if the size of its smaller side is at most k (called k-size) or exactly k (called Ek-size), where k is an input parameter. An s-t cut (A, B) is called unbalanced if its s-side is of k-size or Ek-size. We consider three types of unbalanced cut problems, in which the quality of a cut is measured with respect to the capacity, the sparsity, and the conductance, respectively. We show that even if the input graph is restricted to be a tree, the Ek-Sparsest Cut problem (to find an Ek-size cut with the minimum sparsity) is still NP-hard. We give a bicriteria approximation algorithm for the k-Sparsest Cut problem (to find a k-size cut with the minimum sparsity), which outputs a cut whose sparsity is at most O(logn) times the optimum and whose smaller side has size at most O(logn)k. As a consequence, this leads to a (O(logn), O(logn))- approximation algorithm for the Min k-Conductance problem (to find a k-size cut with the minimum conductance). We also prove that the Min k-Size s-t Cut problem is NP-hard and give an O(logn)-approximation algorithm for it. © 2010 Springer-Verlag.
CITATION STYLE
Li, A., & Zhang, P. (2010). Unbalanced graph partitioning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6506 LNCS, pp. 218–229). https://doi.org/10.1007/978-3-642-17517-6_21
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