# Simple Classification using Binary Data

arXiv: https://arxiv.org/abs/1707.01945 · HTML: https://mlsanity.com/paper/1707.01945/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jul 2017.

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

- [Approximation and generalization properties of the random projection classification method](https://mlsanity.com/paper/2108.06339/) (2021)

## Abstract (arXiv)

Binary, or one-bit, representations of data arise naturally in many applications, and are appealing in both hardware implementations and algorithm design. In this work, we study the problem of data classification from binary data and propose a framework with low computation and resource costs. We illustrate the utility of the proposed approach through stylized and realistic numerical experiments, and provide a theoretical analysis for a simple case. We hope that our framework and analysis will serve as a foundation for studying similar types of approaches.