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https://issues.apache.org/jira/browse/MATH-321?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12795630#action_12795630
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Luc Maisonobe commented on MATH-321:
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A partial fix as been committed in subversion repository as of r894908.
The current implementation computes either the compact SVD (considering only
positive singular values) or the truncated SVD (considering a user-specified
maximal number of singular values).
The issue is however not completely solved yet as the underlying
eigendecomposition still computes all eigenvalues,. The SVD upper layer only
truncates this computation afterwards. This means lots of things are computed
just to be discarded later.
I'll take care of this shortly.
Also note that this implementation still considers only dense matrices, not
sparse ones. Any contributions for sparse SVD is welcome!
> Support for Sparse (Thin) SVD
> -----------------------------
>
> Key: MATH-321
> URL: https://issues.apache.org/jira/browse/MATH-321
> Project: Commons Math
> Issue Type: New Feature
> Reporter: David Jurgens
>
> Current the SingularValueDecomposition implementation computes the full SVD.
> However, for some applications, e.g. LSA, vision applications, only the most
> significant singular values are needed. For these applications, the full
> decomposition is impractical, and for large matrices, computationally
> infeasible. The sparse SVD avoids computing the unnecessary data, and more
> importantly, has significantly lower computational complexity, which allows
> it to scale to larger matrices.
> Other linear algebra implementation have support for the sparse svd. Both
> Matlab and Octave have the svds function. C has SVDLIBC. SVDPACK is also
> available in Fortran and C. However, after extensive searching, I do not
> believe there is any existing Java-based sparse SVD implementation. This
> added functionality would be widely used for any pure Java application that
> requires a sparse SVD, as the only current solution is to call out to a
> library in another language.
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