Hi, Thanks for the offer.
Do you have benchmarks comparing the SPGL1 solver to scikit-learn's? Do you know which class of algorithm the SPGL1 solver uses? Cheers, Gaël On Sat, Mar 21, 2015 at 09:49:01AM -0700, David Relyea wrote: > Hi all, > I recently ported the Matlab version of SPGL1 to python. SPGL1 is an extremely > fast L1 solver (compressive sensing) that is fantastic with very large > datasets > and also handles complex numbers naturally. It has previously only been > available in Matlab. > I'm a capable programmer and can refactor and comment it to follow all > scikit-learn guidelines, but I'd like to know if it would be a welcome > addition. I have permission from the creators to release it. They put it under > the LGPL license, so I'd have to figure out whether there are any issues > changing it over to BSD. Otherwise, it should be fine. > Thanks for any and all guidance. > (As an aside, I'm also going to port NESTA, which is an even faster L1 solver > with somewhat better performance. Once it's ported and I have permissions, I'd > be happy to add it to scikit-learn as well.) > David Relyea > On Sat, Mar 21, 2015 at 9:32 AM, David Relyea <drrel...@gmail.com> wrote: > Hi all, > I recently ported the Matlab version of SPGL1 to python. SPGL1 is an > extremely fast L1 solver (compressive sensing) that is fantastic with very > large datasets and also handles complex numbers naturally. It has > previously only been available in Matlab. > I'm a capable programmer and can refactor it to follow all scikit-learn > guidelines, but I'd like to know if it would be a welcome addition. I have > permission from the creators to release it. They put it under the LGPL > license, so I'd have to know whether there are any issues changing it over > to BSD. Otherwise, it should be fine. > Thanks for any and all guidance. > (As an aside, I'm also going to port NESTA, which is an even faster L1 > solver with somewhat better performance. I'm happy to add either or both > of > them to scikit if desired.) > David Relyea > ------------------------------------------------------------------------------ > Dive into the World of Parallel Programming The Go Parallel Website, sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for all > things parallel software development, from weekly thought leadership blogs to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/ > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- Gael Varoquaux Researcher, INRIA Parietal Laboratoire de Neuro-Imagerie Assistee par Ordinateur NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France Phone: ++ 33-1-69-08-79-68 http://gael-varoquaux.info http://twitter.com/GaelVaroquaux ------------------------------------------------------------------------------ Dive into the World of Parallel Programming The Go Parallel Website, sponsored by Intel and developed in partnership with Slashdot Media, is your hub for all things parallel software development, from weekly thought leadership blogs to news, videos, case studies, tutorials and more. Take a look and join the conversation now. http://goparallel.sourceforge.net/ _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
