# Graph-Sparse Logistic Regression

arXiv: https://arxiv.org/abs/1712.05510 · HTML: https://mlsanity.com/paper/1712.05510/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Dec 2017.

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

- [On Regularized Sparse Logistic Regression](https://mlsanity.com/paper/2309.05925/) (2023)

## Abstract (arXiv)

We introduce Graph-Sparse Logistic Regression, a new algorithm for classification for the case in which the support should be sparse but connected on a graph. We val- idate this algorithm against synthetic data and benchmark it against L1-regularized Logistic Regression. We then explore our technique in the bioinformatics context of proteomics data on the interactome graph. We make all our experimental code public and provide GSLR as an open source package.