# Lower Bound on the Greedy Approximation Ratio for Adaptive Submodular Cover

arXiv: https://arxiv.org/abs/2405.14995 · HTML: https://mlsanity.com/paper/2405.14995/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 8 references that are in the map.
- First posted on arXiv 23 May 2024.

## Builds on (most cited first, 2 of 2)

- [Minimum Cost Adaptive Submodular Cover](https://mlsanity.com/paper/2208.08351/) (2022)
- [A Tight Bound for Stochastic Submodular Cover](https://mlsanity.com/paper/2102.01149/) (2021)

## Built on by (most cited first, 1 of 1)

- [Cost-Aware Recovery-Pathway Identification and Bayesian Optimization for Autonomous Materials Discovery](https://mlsanity.com/paper/2607.23896/) (2026)

## Abstract (arXiv)

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.