# Epsilon-approximations and epsilon-nets

arXiv: https://arxiv.org/abs/1702.03676 · HTML: https://mlsanity.com/paper/1702.03676/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Feb 2017.

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

- [Uniform Brackets, Containers, and Combinatorial Macbeath Regions](https://mlsanity.com/paper/2111.10048/) (2021)

## Abstract (arXiv)

The use of random samples to approximate properties of geometric configurations has been an influential idea for both combinatorial and algorithmic purposes. This chapter considers two related notions---ε-approximations and ε-nets---that capture the most important quantitative properties that one would expect from a random sample with respect to an underlying geometric configuration.