THe problem is that the L^0 norm was being used and it was implemented
assuming that the sparse vector data structure could be queried to find the
number of zeroes.
This is, of course, incorrect. The data structure can only give an upper
bound on the number of nonzero elements.
The other part of the problem was that L^0 was probably not the right
normalization to use.
On Thu, May 28, 2009 at 12:07 AM, Sean Owen <srowen@gmail.com> wrote:
> (Sorry if I am misunderstanding the question or calculation.)
>
> I think your point is, in a sparse vector, shouldn't we ignore the
> 'fake' zeroes we observe where vectors are missing an element?
>
