Re: [eigen] ISO C++ working groups on Linear Algebra / Machine Learning |

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*To*: eigen <eigen@xxxxxxxxxxxxxxxxxxx>*Subject*: Re: [eigen] ISO C++ working groups on Linear Algebra / Machine Learning*From*: Gael Guennebaud <gael.guennebaud@xxxxxxxxx>*Date*: Thu, 14 Feb 2019 19:02:52 +0100*Dkim-signature*: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20161025; h=mime-version:references:in-reply-to:from:date:message-id:subject:to; bh=PEJDaPtHwgurdHPcFDhwOCP8s/KtXTPJkzZGrnLOuXg=; b=EE/UNg+L3AZJSf5UlGqS68WBXT707bSji/wq1mL9Wt9XsAPjufuyF5sgWbSAHXI8Vm 5pRQyknZV1vnehBA00x1BRna2QeTXt/moUUbxys/ehT4nK3r3XNMETNeD0c/9KVG7Gif TWCp5rJOsC2UJWhab4wQttwhzFyWPAMy0XmO0DFu82bL5ZrZC2cdioVnyEBeCOsLu6h0 ypa9fOYRI0if3MPTS/6x6JydQXP4HCIkmA9X493C73gnbfVMNJNoymbTRuhJrOuyKQtX JDtd/M4MJ934RGtq5OQ1zaPjc/aQiqvorp+mrj/W264wSIWMcIYfiCSR7UtcEVuiDd6O fxoQ==

Hi Patrik,

On Wed, Feb 13, 2019 at 6:19 PM Patrik Huber <patrikhuber@xxxxxxxxx> wrote:

I recently found out that the C++ standardisation committee now created a Special Interest Group (SIG) for Linear Algebra within SG14 (the study group for game-dev & low-latency), and that there's also a new study group on machine learning, SG19.Both groups have been formed within the last few months, and I don't think there was too much noise around it, so I thought it might be quite interesting for some people on the Eigen list. I also just joined their forums/list,

Thanks a lot for these informations! I joined both SG14 and SG19 lists too.

and I didn't recognise any familiar name for the Eigen list so far.

There is Matthieu Brucher who is a member of this list and posted here a few times.

On a first glance, I saw that they seem to make a few design decisions that are different from Eigen (e.g. operator* is only for scalar multiplications; or there are separate row/col_vector classes currently).

Regarding operator*, from their discussions we can already see clear disagreements between "linear algebra" people and more general "data scientists"... Some cannot stand operator* as being a matrix-matrix product and are basically seeking for a Numpy on steroid. Personally, as I mostly do linear algebra I almost never use the component-wise product and I'd have a hard time giving up operator* for matrix-matrix products. On the other hand, I found myself using .array() frequently for scalar addition, abs, min/max and comparisons... and I've to admit that our .array()/.matrix() approach is not ideal in this respect.

Nevertheless, following the idea of a "numpy on steroid", if that's really what developers want, we might thought about making our "array world" world more friendly with the linear-algebra world by:

- adding a prod(,) (or dot(,)) function

- moving more MatrixBase functions to DenseBase (most of them could except inverse())

- allowing Array<> as input of decompositions

- enabling "safe" binary operations between Array and Matrix (and returning an Array)

This way people who don't want operator as a matrix product, or with a strong experience of numpy, could simply forget about Matrix<>/.matrix()/.array() and exclusively use Array<>. Then time will tell us if, as with numpy::matrix vs numpy::array, everybody will give up about Matrix<>... (I strongly doubt).

Gaël.

I think it would be really great to get some people from Eigen (us!) aboard that process.Here are some links:SG14 mailing list: http://lists.isocpp.org/sg14/SG19 mailing list: https://groups.google.com/a/isocpp.org/forum/?fromgroups#!forum/sg19There are two repos where they started mapping out ideas/code/paper:Best wishes,Patrik--Dr. Patrik HuberFounder & CEO 4dface Ltd3D face models & personal 3D face avatars for professional applicationsUnited KingdomWeb: www.4dface.io

**Follow-Ups**:**Re: [eigen] ISO C++ working groups on Linear Algebra / Machine Learning***From:*Patrik Huber

**Re: [eigen] ISO C++ working groups on Linear Algebra / Machine Learning***From:*Matthieu Brucher

**References**:**[eigen] ISO C++ working groups on Linear Algebra / Machine Learning***From:*Patrik Huber

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