[SciPy-Dev] Randomized linear algebra functionality

[Ralf Gommers]

On Sat, Sep 15, 2018 at 2:30 AM Touqir Sajed <touqir at ualberta.ca> wrote:

> There seems to be some interest in implementing randomized linear algebra
> algorithms such as JL transformation, low-rank approximation, etc as
> written in  https://github.com/scipy/scipy/wiki/GSoC-2018-project-ideas
> <https://ml-trckr.com/link/https%3A%2F%2Fgithub.com%2Fscipy%2Fscipy%2Fwiki%2FGSoC-2018-project-ideas/cBzmzxqJ6V7Fi58kyipk>
> . To the best of my knowledge, they are not implemented yet. If there still
> exists interests I would like to implement the Fast JL transformation and
> the randomized SVD for low-rank approximation. The pseudo code of Fast JL
> transformation is given here:
> https://pdfs.semanticscholar.org/ccf0/1e0375d11df5335b645161b4833e32380d89.pdf
> <https://ml-trckr.com/link/https%3A%2F%2Fpdfs.semanticscholar.org%2Fccf0%2F1e0375d11df5335b645161b4833e32380d89.pdf/cBzmzxqJ6V7Fi58kyipk>
> . The randomized SVD is based on https://arxiv.org/pdf/0909.4061.pdf
> <https://ml-trckr.com/link/https%3A%2F%2Farxiv.org%2Fpdf%2F0909.4061.pdf/cBzmzxqJ6V7Fi58kyipk>
> .
>

Hi Touqir. The problem with randomized linear algebra is that there's no
core developer with the knowledge and interest to work on this. That GSoC
proposal never materialized. So I suspect that while there's interest from
users, PRs will be difficult to get merged. A better approach here may be
to implement these methods in a separate package, and once that stabilized
and has gained users, then revisit whether it can be incorporated into
SciPy.

Cheers,
Ralf
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scipy-dev/attachments/20180915/08822772/attachment.html>