# Neighborhood density estimation using space-partitioning based hashing schemes

arXiv: https://arxiv.org/abs/2512.03187 · HTML: https://mlsanity.com/paper/2512.03187/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2025.

## Abstract (arXiv)

This work introduces FiRE/FiRE.1, a novel sketching-based algorithm for anomaly detection to quickly identify rare cell sub-populations in large-scale single-cell RNA sequencing data. This method demonstrated superior performance against state-of-the-art techniques. Furthermore, the thesis proposes Enhash, a fast and resource-efficient ensemble learner that uses projection hashing to detect concept drift in streaming data, proving highly competitive in time and accuracy across various drift types.