Thanks.
yes, there are tricks but that would change SVD contract and amend the
method, which is why I asked "without changing SVD contract", i.e.
without changing what A, U, Sigma and V mean in SVD step.
But assuming we'd want to integrate PCA with the method, i guess yes
special treatment of a mean side info could be devised.
On Tue, Sep 6, 2011 at 12:35 PM, Ted Dunning <ted.dunning@gmail.com> wrote:
> Another option is to invent another kind of matrix that knows about an
> offset. Then a special method for times may give the right performance.
>
> A third option is to do a little algebra on the PCA algorithm to propagate
> the mean offset into the stochastic projection algorithm.
>
> On Tue, Sep 6, 2011 at 7:24 PM, Ted Dunning <ted.dunning@gmail.com> wrote:
>
>> Sure.
>>
>> Do the subtraction after the B = Q'A step in the random projection!
>>
>> On Tue, Sep 6, 2011 at 7:16 PM, Dmitriy Lyubimov <dlieu.7@gmail.com>wrote:
>>
>>> On Tue, Sep 6, 2011 at 12:11 PM, Ted Dunning <ted.dunning@gmail.com>
>>> wrote:
>>> > Note that normally subtracting anything fills in sparse matrices.
>>>
>>> is there a way to cope with this without changing SVD contracts?
>>>
>>
>>
>
