[GSoC 2019] Matrix pseudoinverse and Least squares solver

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Hi all,

I was investigating some methods to perform least squares algorithms, and I
noticed we currently do not have methods of doing so in the development
branch.

To the extent of my knowledge, we also do not have a method of determining
matrix inverses or pseudoinverse. All of the existing implementations I
found (e.g. rTensor) of CP decomposition have a method of determining a
matrix's pseudoinverse.

For GSoC, I initially based my proposal around implementing tensor
decomposition algorithms. However, would it be a better choice to focus
more on least squares methods like QR-factorization=E2=80=9D And SVD? Furth=
ermore,
was this already attempted in a past GSoC project?

Thanks,

Thomas

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<div dir=3D"ltr">Hi all,<br><br>I was investigating some methods to perform=
 least squares algorithms, and I noticed we currently do not have methods o=
f doing so in the development branch.=C2=A0<br><br>To the extent of my know=
ledge, we also do not have a method of determining matrix inverses or pseud=
oinverse. All of the existing implementations I found (e.g. rTensor) of CP =
decomposition have a method of determining a matrix&#39;s pseudoinverse.=C2=
=A0<br><br>For GSoC, I initially based my proposal around implementing tens=
or decomposition algorithms. However, would it be a better choice to focus =
more on least squares methods like QR-factorization=E2=80=9D And SVD? Furth=
ermore, was this already attempted in a past GSoC project?<br><br>Thanks,<b=
r><br>Thomas=C2=A0=C2=A0<br></div>

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