An Analysis of Approximations for Maximizing Submodular Set Functions—I¶
Nemhauser, G. L., Wolsey, L. A., & Fisher, M. L. (1978). An Analysis of Approximations for Maximizing Submodular Set Functions—I. Mathematical Programming, 14(1), 265-294.
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Mechanisms¶
- Highest-Marginal-Gain-First Rule
- On the well-behaved case — a monotone, submodular objective under a size budget — greedy marginal selection is provably within a constant factor, about 63%, of the best possible set.
This sourceProves that greedy marginal selection achieves a 1−1/e, approximately 63 percent, guarantee for monotone submodular maximization under a size constraint.
- On the well-behaved case — a monotone, submodular objective under a size budget — greedy marginal selection is provably within a constant factor, about 63%, of the best possible set.
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Registry ID ref:0ae7455fb034 · see in the full table