Feature Space Sketching for Logistic Regression

Gregory Dexter, Rajiv Khanna, Jawad Raheel, Petros Drineas
3/24/2023
cs.LGstat.ML

No confident code implementation found for this paper.

Abstract

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{dexter2023feature,
  title  = {Feature Space Sketching for Logistic Regression},
  author = {Gregory Dexter and Rajiv Khanna and Jawad Raheel and Petros Drineas},
  year   = {2023},
  eprint = {2303.14284},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.14284v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2303.14284.svg)](https://codeofpaper.com/paper/2303.14284)

Discussion