How to Simulate A la Carte

[FBoyang]

Dear Project developers:

Thank you for providing such a great tool. I am currently testing the "A la Carte" method proposed by Zichao Yang et al. And I notice that you mention in your report that A la Carte is implemented in your software. Therefore I attempted to use randomRBF basis and standard linear model to learn the kernel. In A la carte, the agnostic kernel matrix is approximated using a mixture of Q different kernels with weight V^2_q/m respectively.

Now I am interested in getting the weight V^2_q/m. I wonder how may I get the weight component of each kernel in your software?

Thank you very much!

[dsteinberg]

Hi Boyang!

Thanks for the compliment, and I'm glad you like this software :-)

Unfortunately we have stopped maintaining this project, and we moved of our efforts to a related project (https://github.com/gradientinstitute/aboleth). Now a lot of this has all been implemented in Tensorflow Probability, and we hardly use aboleth too. It has been quite a few years since I have looked at this codebase, and I cannot remember if we ever implemented the full "a la carte" model, I think the furthest we got was documented in this notebook:

https://github.com/NICTA/revrand/blob/master/demos/alacarte_kernels.ipynb

I think manually managing all of these gradients became too much in the end, which is why we made the move to auto-diff libraries.

I'm sorry I can't be of more assistance. Good luck in your efforts!

[FBoyang]

Hi Daniel:

Thank you very much for your reply! I really appreciate it and will pay close attention to your new project!

Best regards
Boyang