Maximization of Approximately Submodular Functions

Thibaut Horel, Yaron Singer
11/1/2024

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Abstract

We study the problem of maximizing a function that is approximately submodular under a cardinality constraint. Approximate submodularity implicitly appears in a wide range of applications as in many cases errors in evaluation of a submodular function break submodularity. Say that $F$ is $\eps$-approximately submodular if there exists a submodular function $f$ such that $(1-\eps)f(S) \leq F(S)\leq (1+\eps)f(S)$ for all subsets $S$. We are interested in characterizing the query-complexity of maximizing $F$ subject to a cardinality constraint $k$ as a function of the error level $\eps > 0$. We provide both lower and upper bounds: for $\eps > n^{-1/2}$ we show an exponential query-complexity lower bound. In contrast, when $\eps < {1}/{k}$ or under a stronger bounded curvature assumption, we give constant approximation algorithms.

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Cite this paper

@article{horel2024maximization,
  title  = {Maximization of Approximately Submodular Functions},
  author = {Thibaut Horel and Yaron Singer},
  year   = {2024},
  eprint = {2411.10949},
  archivePrefix = {arXiv},
  doi    = {10.48550/arXiv.2411.10949},
  url    = {https://arxiv.org/abs/2411.10949},
  journal = {NEURIPS 2024 2024}
}

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