Monotone Submodular Multiway Partition
Richard Bi, Karthekeyan Chandrasekaran, Soham Joshi

TL;DR
This paper studies the problem of partitioning a set to minimize a monotone submodular function, providing approximation algorithms and hardness results, and introduces a special case related to graph coverage with tighter bounds.
Contribution
It presents the first approximation algorithms for monotone submodular multiway partition and its special case, graph coverage, along with hardness results under the Unique Games Conjecture.
Findings
Monotone submodular multiway partition admits a 4/3-approximation.
No $(10/9 - \epsilon)$-approximation exists for the general problem.
Graph coverage multiway partition admits a 1.125-approximation and is hard to approximate within 1.00074 assuming UGC.
Abstract
In submodular multiway partition (SUB-MP), the input is a non-negative submodular function given by an evaluation oracle along with terminals . The goal is to find a partition of with for every in order to minimize . In this work, we focus on SUB-MP when the input function is monotone (termed MONO-SUB-MP). MONO-SUB-MP formulates partitioning problems over several interesting structures -- e.g., matrices, matroids, graphs, and hypergraphs. MONO-SUB-MP is NP-hard since the graph multiway cut problem can be cast as a special case. We investigate the approximability of MONO-SUB-MP: we show that it admits a -approximation and does not admit a -approximation for every constant . Next, we study a special case of…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · graph theory and CDMA systems · Computational Geometry and Mesh Generation
