# Distribution-free Detection of a Submatrix

arXiv: https://arxiv.org/abs/1604.07449 · HTML: https://mlsanity.com/paper/1604.07449/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Apr 2016.

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

- [Lattice partition recovery with dyadic CART](https://mlsanity.com/paper/2105.13504/) (2021)

## Abstract (arXiv)

We consider the problem of detecting the presence of a submatrix with larger-than-usual values in a large data matrix. This problem was considered in (Butucea and Ingster, 2013) under a one-parameter exponential family, and one of the test they analyzed is the scan test. Taking a nonparametric stance, we show that a calibration by permutation leads to the same (first-order) asymptotic performance. This is true for the two types of permutations we consider. We also study the corresponding rank-based variants and precisely quantify the loss in asymptotic power.