# Feature Space Sketching for Logistic Regression

arXiv: https://arxiv.org/abs/2303.14284 · HTML: https://mlsanity.com/paper/2303.14284/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 41 references that are in the map.
- First posted on arXiv 24 Mar 2023.

## Builds on (most cited first, 12 of 12)

- [Sketching as a Tool for Numerical Linear Algebra](https://mlsanity.com/paper/1411.4357/) (2014)
- [On Coresets for Logistic Regression](https://mlsanity.com/paper/1805.08571/) (2018)
- [Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima](https://mlsanity.com/paper/1305.2436/) (2013)
- [Restricted Strong Convexity Implies Weak Submodularity](https://mlsanity.com/paper/1612.00804/) (2016)
- [Determinantal Point Processes in Randomized Numerical Linear Algebra](https://mlsanity.com/paper/2005.03185/) (2020)
- [Iterative Hessian sketch: Fast and accurate solution approximation for constrained least-squares](https://mlsanity.com/paper/1411.0347/) (2014)
- [Coresets for Classification -- Simplified and Strengthened](https://mlsanity.com/paper/2106.04254/) (2021)
- [Randomized Sketches of Convex Programs with Sharp Guarantees](https://mlsanity.com/paper/1404.7203/) (2014)
- [Lectures on Randomized Numerical Linear Algebra](https://mlsanity.com/paper/1712.08880/) (2017)
- [Oblivious sketching for logistic regression](https://mlsanity.com/paper/2107.06615/) (2021)
- [Tight Bounds for the Subspace Sketch Problem with Applications](https://mlsanity.com/paper/1904.05543/) (2019)
- [Subsampling for Ridge Regression via Regularized Volume Sampling](https://mlsanity.com/paper/1710.05110/) (2017)

## Built on by (most cited first, 4 of 4)

- [Scalable Learning of Item Response Theory Models](https://mlsanity.com/paper/2403.00680/) (2024)
- [A Provably Accurate Randomized Sampling Algorithm for Logistic Regression](https://mlsanity.com/paper/2402.16326/) (2024)
- [Data subsampling for Poisson regression with pth-root-link](https://mlsanity.com/paper/2410.22872/) (2024)
- [A Logistic Regression Model to Predict Malaria Severity in Children](https://mlsanity.com/paper/2605.18900/) (2026)

## Abstract (arXiv)

We present novel bounds for coreset construction, feature selection, and dimensionality reduction for logistic regression. All three approaches can be thought of as sketching the logistic regression inputs. On the coreset construction front, we resolve open problems from prior work and present novel bounds for the complexity of coreset construction methods. On the feature selection and dimensionality reduction front, we initiate the study of forward error bounds for logistic regression. Our bounds are tight up to constant factors and our forward error bounds can be extended to Generalized Linear Models.