- "Dimitri Pourbaix" a écrit :
> Luc,
>
> > I think there are two parts in the isse.
> > The first one is related to sparse matrix and we don't have an
> answer
> > yet. The second part is related to compute a partial set of
> singular
> > values. This is used for example in image compressi
Computation of the largest few singular values (often associated with a
partial set of singular vectors, either left, right or both) is very much
the business of the SVD algorithm because computing just a few singular
values is much more efficient than computing the entire set and often
suffices ju
For sparse matrices, almost the only requirement is a good dense SVD. If
you have an SVD that is very fast for tall skinny matrices, that would be
excellent. If not, that can be worked around.
The basic idea is that right multiplication by a tall skinny random array
(which is never stored explic
Luc,
I think there are two parts in the isse.
The first one is related to sparse matrix and we don't have an answer
yet. The second part is related to compute a partial set of singular
values. This is used for example in image compression or to find a
matrix with reduce rank that is the closest
Dimitri Pourbaix a écrit :
> Luc,
>
>> Concerning MATH-321, the partial fix I proposed has been withdrawn by
>> the complete rewrite of SVD.
>> This partial fix also was not considered mathematically sound by Dimitri
>> since the dimensions of the matrices did not match complete SVD. Well,
>> this
Luc,
Concerning MATH-321, the partial fix I proposed has been withdrawn by
the complete rewrite of SVD.
This partial fix also was not considered mathematically sound by Dimitri
since the dimensions of the matrices did not match complete SVD. Well,
this was in fact desired as MATH-321 explicitly
Phil Steitz a écrit :
> Phil Steitz wrote:
>> Phil Steitz wrote:
>>> luc.maison...@free.fr wrote:
- "Phil Steitz (JIRA)" a écrit :
> [
> https://issues.apache.org/jira/browse/MATH-282?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
> ]
>
> Phil S
Phil Steitz wrote:
> Phil Steitz wrote:
>> luc.maison...@free.fr wrote:
>>> - "Phil Steitz (JIRA)" a écrit :
>>>
[
https://issues.apache.org/jira/browse/MATH-282?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Phil Steitz resolved MATH-282.
---
Gilles Sadowski wrote:
> Hi.
>
>> [...] OLS regression (350 - good catch!) also
>> obviously needs to be fixed. Thanks to all for testing.
>
> There is indeed a difference from what CM 2.0 computed but maybe that it is
> not a problem after all, and is just to be expected from the implementatio
Hi.
> [...] OLS regression (350 - good catch!) also
> obviously needs to be fixed. Thanks to all for testing.
There is indeed a difference from what CM 2.0 computed but maybe that it is
not a problem after all, and is just to be expected from the implementation
change: some failing tests compar
Phil Steitz wrote:
> luc.maison...@free.fr wrote:
>> - "Phil Steitz (JIRA)" a écrit :
>>
>>> [
>>> https://issues.apache.org/jira/browse/MATH-282?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
>>> ]
>>>
>>> Phil Steitz resolved MATH-282.
>>> --
>>
Gilles Sadowski wrote:
> Hello.
>
>> [...]
>>
>>> With this fix, there are no pending issues for 2.1. Gilles is working on
>>> two unscheduled issues.
>>> I suggest once he has committed the fixes, we can go ahead to release 2.1.
>>>
>>> Any thoughts about this ?
>> First, let me volunteer to RM.
Hello.
> [...]
>
> > With this fix, there are no pending issues for 2.1. Gilles is working on
> > two unscheduled issues.
> > I suggest once he has committed the fixes, we can go ahead to release 2.1.
> >
> > Any thoughts about this ?
>
> First, let me volunteer to RM. [...]
May I suggest to
luc.maison...@free.fr wrote:
> - "Phil Steitz (JIRA)" a écrit :
>
>> [
>> https://issues.apache.org/jira/browse/MATH-282?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
>> ]
>>
>> Phil Steitz resolved MATH-282.
>> --
>>
>> Resolution: Fixed
>
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