# Random Polytope Descriptors

arXiv: https://arxiv.org/abs/2009.13987 · HTML: https://mlsanity.com/paper/2009.13987/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 33 references that are in the map.
- First posted on arXiv 29 Sep 2020.

## Builds on (most cited first, 1 of 1)

- [Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms](https://mlsanity.com/paper/1708.07747/) (2017)

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

- [CHA2: CHemistry Aware Convex Hull Autoencoder Towards Inverse Molecular Design](https://mlsanity.com/paper/2302.11000/) (2023)

## Abstract (arXiv)

We introduce a class of random polytopes which simultaneously generalizes several known constructions. While being fairly general, these polytopes are also computationally exceptionally benign. We indicate how these properties can be exploited for classification and clustering tasks in data analysis. Crucially, our construction lets users smoothly trade off between a tighter description of the data and faster computation.