# Spectral Toolkit of Algorithms for Graphs: Technical Report (2)

arXiv: https://arxiv.org/abs/2407.07096 · HTML: https://mlsanity.com/paper/2407.07096/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 32 references that are in the map.
- First posted on arXiv 6 Jun 2024.

## Builds on (most cited first, 9 of 9)

- [Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs](https://mlsanity.com/paper/1603.09320/) (2016)
- [Practical and Optimal LSH for Angular Distance](https://mlsanity.com/paper/1509.02897/) (2015)
- [Optimal Data-Dependent Hashing for Approximate Near Neighbors](https://mlsanity.com/paper/1501.01062/) (2015)
- [Hashing-Based-Estimators for Kernel Density in High Dimensions](https://mlsanity.com/paper/1808.10530/) (2018)
- [Kernel Density Estimation through Density Constrained Near Neighbor Search](https://mlsanity.com/paper/2011.06997/) (2020)
- [Distributed Graph Clustering and Sparsification](https://mlsanity.com/paper/1711.01262/) (2017)
- [Faster Kernel Matrix Algebra via Density Estimation](https://mlsanity.com/paper/2102.08341/) (2021)
- [Spectral Toolkit of Algorithms for Graphs: Technical Report (1)](https://mlsanity.com/paper/2304.03170/) (2023)
- [Fast Approximation of Similarity Graphs with Kernel Density Estimation](https://mlsanity.com/paper/2310.13870/) (2023)

## Abstract (arXiv)

Spectral Toolkit of Algorithms for Graphs (STAG) is an open-source library for efficient graph algorithms. This technical report presents the newly implemented component on locality sensitive hashing, kernel density estimation, and fast spectral clustering. The report includes a user's guide to the newly implemented algorithms, experiments and demonstrations of the new functionality, and several technical considerations behind our development.