On Tue, Dec 8, 2009 at 6:47 PM, Zhengguo 'Mike' SUN
<zhengguosun@yahoo.com>wrote:
> Hi Jake,
>
> I am implementing the classical multiplicative update rule of NMF. The
> matrix to be factorized is really big and sparse. Are you suggesting that I
> can use some specialised algorithms for sparse matrix instead of the
> standard multiplication algorithm? But what algorithms are you referring to?
> Could you please provide some pointers?
>
So given your input matrix X, you're trying to find nonnegative matrices W
(thin matrix, with few long dense columns) and H (wide matrix, with few long
dense rows) which minimize  X  WH , right, where  *  is the
Froebenius norm, right?
I'm just suggesting that you don't even compute entries in X  WH where X
has missing data  optimize treating those values as unknown, not "zero".
jake
