This is a repo for Julia implementation of Maxvolrelated algorithms.
Maxvol is an algorithm which finds a submatrix of quasimaximum volume in a given matrix. Submatrices of maximum volume play crucial role in lowrank cross (interpolative) approximations as well as in different optimization problems. More on this can be found in the following literature:

S.A. Goreinov, N.L. Zamarashkin and E.E. Tyrtyshnikov, 1997. Pseudoskeleton approximations by matrices of maximal volume. In Mathematical Notes, 62(4), (pp. 515519).

S.A. Goreinov, E.E. Tyrtyshnikov and N.L. Zamarashkin, 1997. A theory of pseudoskeleton approximations. In Linear algebra and its applications, 261(13), (pp. 121).

S.A. Goreinov, I.V. Oseledets, D.V. Savostyanov, E.E. Tyrtyshnikov and N.L. Zamarashkin, 2010. How to find a good submatrix. In Matrix Methods: Theory, Algorithms And Applications: Dedicated to the Memory of Gene Golub (pp. 247256).

I. Oseledets and E. Tyrtyshnikov, 2010. TTcross approximation for multidimensional arrays. In Linear Algebra and its Applications, 432(1), (pp. 7088).

D.V. Savostyanov, 2014. Quasioptimality of maximumvolume cross interpolation of tensors. In Linear Algebra and its Applications, 458, (pp. 217244).

N.L. Zamarashkin and A.I. Osinsky, 2016. New accuracy estimates for pseudoskeleton approximations of matrices. In Doklady Mathematics (Vol. 94, No. 3, pp. 643645).

A.I. Osinsky and N.L. Zamarashkin, 2018. Pseudoskeleton approximations with better accuracy estimates. In Linear Algebra and its Applications, 537, (pp. 221249).

A. Mikhalev and I.V. Oseledets, 2018. Rectangular maximumvolume submatrices and their applications. In Linear Algebra and its Applications, 538, (pp. 187211).
As it is a Julia package, it can be installed with a simple
julia> using Pkg
julia> Pkg.add("https://github.com/muxas/maxvol.jl")
Is available online here.