Corpus ID: 199442267

Fast Evolutionary Algorithms for Maximization of Cardinality-Constrained Weakly Submodular Functions

@article{Crawford2019FastEA,
  title={Fast Evolutionary Algorithms for Maximization of Cardinality-Constrained Weakly Submodular Functions},
  author={Victoria G. Crawford and Alan Kuhnle},
  journal={ArXiv},
  year={2019},
  volume={abs/1908.01230}
}
  • Victoria G. Crawford, Alan Kuhnle
  • Published in ArXiv 2019
  • Computer Science, Mathematics
  • We study the monotone, weakly submodular maximization problem (WSM), which is to find a subset of size $k$ from a universe of size $n$ that maximizes a monotone, weakly submodular objective function $f$. For objectives with submodularity ratio $\gamma$, we provide two novel evolutionary algorithms that have an expected approximation guarantee of $(1-n^{-1})(1-e^{-\gamma}-\epsilon)$ for WSM in linear time, improving upon the cubic time complexity of previous evolutionary algorithms for this… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 32 REFERENCES

    Fast algorithms for maximizing submodular functions

    VIEW 9 EXCERPTS
    HIGHLY INFLUENTIAL

    Maximizing the Spread of Influence through a Social Network

    VIEW 9 EXCERPTS
    HIGHLY INFLUENTIAL

    Lazier Than Lazy Greedy

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL