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1  Introduction

SPAMS (SPArse Modeling Software) is an open-source optimization toolbox for sparse estimation with licence GPLv3. It implements algorithms for solving machine learning and signal processing problems involving sparse regularizations.

The library is coded in C++, is compatible with Linux, Mac, and Windows 32bits and 64bits Operating Systems. It is interfaced with Matlab, R and Python, but can be called from any C++ application (by hacking the code a bit).

It requires an implementation of BLAS and LAPACK for performing linear algebra operations. The ones shipped with matlab and R can be used, but also external libraries such as atlas, the netlib implementation, or the Intel Math Kernel Library can be used. It also exploits multi-core CPUs when this feature is supported by the compiler, through OpenMP.

The current licence is GPLv3, which is available at For other licensing possibilities allowing its use in proprietary softwares, please contact the author.

Version 2.5 of SPAMS is divided into several “toolboxes” and has a few additional miscellaneous functions:

The toolbox was written by Julien Mairal at INRIA, with the collaboration of Francis Bach (INRIA), Jean Ponce (Ecole Normale Supérieure), Guillermo Sapiro (University of Minnesota), Guillaume Obozinski (INRIA) and Rodolphe Jenatton (INRIA).

R and Python interfaces have been written by Jean-Paul Chieze (INRIA). The archetypal analysis implementation was written by Yuansi Chen, during an internship at INRIA, with the collaboration of Zaid Harchaoui.

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