# Query Minimization under Stochastic Uncertainty

arXiv: https://arxiv.org/abs/2010.03517 · HTML: https://mlsanity.com/paper/2010.03517/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Oct 2020.

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

- [Sorting and Hypergraph Orientation under Uncertainty with Predictions](https://mlsanity.com/paper/2305.09245/) (2023)

## Abstract (arXiv)

We study problems with stochastic uncertainty information on intervals for which the precise value can be queried by paying a cost. The goal is to devise an adaptive decision tree to find a correct solution to the problem in consideration while minimizing the expected total query cost. We show that, for the sorting problem, such a decision tree can be found in polynomial time. For the problem of finding the data item with minimum value, we have some evidence for hardness. This contradicts intuition, since the minimum problem is easier both in the online setting with adversarial inputs and in the offline verification setting. However, the stochastic assumption can be leveraged to beat both deterministic and randomized approximation lower bounds for the online setting.