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Lower Bound on the Greedy Approximation Ratio for Adaptive Submodular Cover

2024-05-23 · Blake Harris, Viswanath Nagarajan

We show that the greedy algorithm for adaptive-submodular cover has approximation ratio at least 1.3*(1+ln Q). Moreover, the instance demonstrating this gap has Q=1. So, it invalidates a prior result in the paper ``Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization'' by Golovin-Krause, that claimed a (1+ln Q)^2 approximation ratio for the same algorithm.

📄 PDF Abstract BibTeX arXiv:2405.14995

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Active LearningStochastic Optimization

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