- $\mathbf{x}\in\mathbb{R}^m$ is the observation vector

- $\mathbf{A}\in\mathbb{R}^{m\times n}$ is the so-called dictionary

- $\lambda>0$ a (positive) scalar

- $\{\gamma_k\}_{k=1}^n$ a sequence of non-increasing nonnegative scalars such that $\gamma_1=1$,

- $\vert\mathbf{x}\vert_{[k]}$ denotes the $k$th largest entry of $\mathbf{x}$ in absolute value

> [1] Clément Elvira, Cédric Herzet: “Safe rules for the identification of zeros in the solution of the Slope problem”, arXiv, septembre 2021; [arXiv:1911.07508](http://arxiv.org/abs/0000.00000)

The above paper contains theoretical results and several applications that can be reproduced with this toolbox.

This python toolbox is currently under development and is hosted on Gitlab. If you encounter a bug or something unexpected please let me know by [raising an issue](https://gitlab-research.centralesupelec.fr/2020elvirac/slope-screening/-/issues) on the project page or by contacting me by mail.