Develops polynomial-time algorithms achieving competitive ratios of ~1/14.85 (general) and 1/6.86 (unit costs) for submodular welfare maximization with budgets under random-order item arrival.
Online Submodular Welfare Maximization: Greedy is Optimal , booktitle =
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A new ordered local search algorithm achieves k/2 + o(k) approximation for monotone submodular maximization over k matroids and (ln 4 k)/3 + o(k) for weighted k-set packing.
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Submodular Welfare Maximization with Budget Constraints in the Random-Order Model
Develops polynomial-time algorithms achieving competitive ratios of ~1/14.85 (general) and 1/6.86 (unit costs) for submodular welfare maximization with budgets under random-order item arrival.
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Submodular Maximization over Many Matroids via Ordered Local Search
A new ordered local search algorithm achieves k/2 + o(k) approximation for monotone submodular maximization over k matroids and (ln 4 k)/3 + o(k) for weighted k-set packing.