[SciPy-Dev] Some remarks on least-squares algorithms

[Carl Kleffner]

I oversight that your problem is non-linear. You may try out DFO-GN:

DFO-GN: A Derivative-Free Gauss-Newton Solver
https://github.com/numericalalgorithmsgroup/dfogn
https://numericalalgorithmsgroup.github.io/dfogn/build/html/index.html

However, I didn't test it myself.

Carl

Am Di., 13. Apr. 2021 um 22:01 Uhr schrieb Carl Kleffner <
cmkleffner at gmail.com>:

> You may take a look at ARLS: Automatically Regularized Linear System
> Solver <https://pypi.org/project/arls/> based on scipy.linalg.
> It is a heuristic solver (using the picard condition) for over-determined
> / under-determined or ill-conditioned problems.
>
> Cheers
>
> Carl
>
> Am Mo., 12. Apr. 2021 um 17:24 Uhr schrieb Robert Kern <
> robert.kern at gmail.com>:
>
>> On Mon, Apr 12, 2021 at 5:30 AM Benoit Rosa <b.rosa at unistra.fr> wrote:
>>
>>>
>>> The second remark is that, when looking at MATLAB's implementation, I
>>> found this:
>>>
>>
>> First, thank you for your comments.
>>
>> Second, I know it seems innocuous, but please do not post snippets of
>> MATLAB's source code here. They are under copyright and presumably MATLAB's
>> proprietary license. We can't refer to that code when writing our own
>> implementation, even if we are just reading this email with the snippet. We
>> can refer to open source code under a liberal license like SciPy's, and we
>> can refer to papers or even MATLAB's documentation that describe the
>> algorithm but not in code. Having the snippet posted here puts us in an
>> awkward position with respect to actually following up on your request.
>>
>> Thank you for your consideration.
>>
>> --
>> Robert Kern
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>> SciPy-Dev at python.org
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>
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