Hello,
there is a nice collection of sparse coding and dictionary algorithms
implemented in scikit-learn. However, it seems there are no
shift-invariant implementations. Are there plans to include any
shift-invariant implementations or is there a way to apply the
implemented algorithms in a shift-invariant manner?
With "shift-invariant" I mean a formulation, where the reconstruction is
done by convolution of the atoms with the coefficients, like
min_{U,V}||X-conv(U,W)||_2^2|| + alpha ||U||_1
I think, I could get shift-invariant behaviour in the coding part by
first building a dictionary of all shifted versions of all atoms and
then apply the implemented sparse coding algorithms. However, I don't
see a shift-invariant way for the dictionary learning part.
Thanks,
Christian
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