[SciPy-User] Sparse Matricies and NNLS
Mon Apr 15 11:34:50 CDT 2013
On Mon, Apr 1, 2013 at 6:07 AM, Calvin Morrison <email@example.com>wrote:
> Tsnnls might have been fast in 2001, trying it on a moderatley sized
> dataset is beyond slow
> On Apr 1, 2013 8:57 AM, "Jonathan Guyer" <firstname.lastname@example.org> wrote:
>> On Mar 28, 2013, at 5:33 PM, Calvin Morrison wrote:
>> > It seems nobody wants to touch the nnls algorithm because the only
>> implementation that is floating around is the one from the original
>> publication or automatic conversions of it.
>> For whatever it's worth, the second google hit for "nnls sparse" is
>> "tsnnls: A solver for large sparse least squares problems with
>> non-negative variables
>> The solution of large, sparse constrained least-squares problems is a
>> staple in scientific and engineering applications. However, currently
>> available codes for such problems are proprietary or based on MATLAB. We
>> announce a freely available C implementation of the fast block pivoting
>> algorithm of Portugal, Judice, and Vicente. Our version is several times
>> faster than Matstoms’ MATLAB implementation of the same algorithm. Further,
>> our code matches the accuracy of MATLAB’s built-in lsqnonneg function."
>> All links to the code seem to be dead, but it's probably worth contacting
>> the authors.
>> SciPy-User mailing list
> SciPy-User mailing list
I've found stochastic gradient descent to be very useful for this kind of
Here's an implementation, adapted from a colleague's Matlab implementation:
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