# Compressive Classification (Machine Learning without learning)

arXiv: https://arxiv.org/abs/1812.01410 · HTML: https://mlsanity.com/paper/1812.01410/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2018.

## Built on by (most cited first, 3 of 3)

- [Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning](https://mlsanity.com/paper/2112.00423/) (2021)
- [Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoising](https://mlsanity.com/paper/2310.03085/) (2023)
- [Compressive Meta-Learning](https://mlsanity.com/paper/2508.11090/) (2025)

## Abstract (arXiv)

Compressive learning is a framework where (so far unsupervised) learning tasks use not the entire dataset but a compressed summary (sketch) of it. We propose a compressive learning classification method, and a novel sketch function for images.