Two-Stage Submodular Maximization Under Knapsack Problem

doi:10.26599/TST.2023.9010107

2024-12-01

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DOI：10.26599/TST.2023.9010107

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基数约束下的两阶段子模最大化问题在机器学习和组合优化中得到了广泛的研究。在本文中，我们考虑背包约束。在这个问题中，我们给出n篇文章和m个类别，目标是选择一个可以最大化函数F(S) 的文章子集。函数F(S) 由m个单调子模函数f(j) 组成，j = 1,2，...，m，每个f(j) 度量j类中每篇文章的相似性。

Keyword:

Machine learning

Approximation algorithms

Optimization

submodular function

knapsack constraint

matroid

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Tsinghua Science and Technology

IF:

3.5

论文数:

987

被引数:

2.5K

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University of New Brunswick

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Beijing University of Technology

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2.8W

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Nanjing Normal University

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1.7W

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