Incremental Submodular Maximization: Better Than Greedy

Abstract

We consider submodular maximization under increasing cardinality constraint and ask for a good incremental solution, i.e., an ordering of the ground set such that each prefix of the ordering yields a good solution for its respective cardinality. A classical result in this setting is that the greedy algorithm achieves a competitive ratio, i.e., an approximation guarantee across all cardinalities, of e/(e-1) ≈ 1.582. No better general guarantee was previously known. We present an adaptive scaling algorithm achieving a competitive ratio of 1.373. We complement our result by a deterministic lower bound of 1.25 on the best possible competitive ratio for incremental submodular maximization.

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