Hi all,
please, check out the repo: github.com/akopich/spark-gp/. I've
implemented the regressor.
Simon, have you still got smth to try it out on?
Best,
Valeriy.
On 02/15/2018 05:16 PM, Аванесов Валерий wrote:
Hi all,
I've created a new JIRA.
https://issues.apache.org/jira/browse/SPARK-
Hi all,
I've created a new JIRA.
https://issues.apache.org/jira/browse/SPARK-23437
All concerned are welcome to discuss.
Best,
Valeriy.
On Sat, Feb 3, 2018 at 9:24 PM, Valeriy Avanesov wrote:
> Hi,
>
> no, I don't thing we should actually compute the n \times n matrix. Leave
> alone invertin
Hi,
no, I don't thing we should actually compute the n \times n matrix.
Leave alone inverting it. However, variational inference is only one of
the many sparse GP approaches. Another option could be Bayesian Committee.
Best,
Valeriy.
On 02/02/2018 09:43 PM, Simon Dirmeier wrote:
Hey,
I w
Hey,
I wanted to see that for a long time, too. :) If you'd plan on
implementing this, I could contribute.
However, I am not too familiar with variational inference for the GPs
which is what you would need I guess.
Or do you think it is feasible to compute the full kernel for the GP?
Cheers,
