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Add implementations for the q- class of acquisition functions (i.e. q-EI), which return a set of q query points which are then run in parallel on the function.
I think implementation-wise this is fairly straightforward. On the interface side, the question is how the user defines the parallel function. I think this should accept any function f which takes a vector of vectors and returns a vector of results, so that the user is free to specify how that parallel operation takes place. I'm open to thoughts on what an automatically parallel interface would look like.
Add implementations for the q- class of acquisition functions (i.e. q-EI), which return a set of q query points which are then run in parallel on the function.
I think implementation-wise this is fairly straightforward. On the interface side, the question is how the user defines the parallel function. I think this should accept any function
f
which takes a vector of vectors and returns a vector of results, so that the user is free to specify how that parallel operation takes place. I'm open to thoughts on what an automatically parallel interface would look like.References:
[1] Wang, Clark, Liu, Frazier. Parallel Bayesian Global Optimization of Expensive Functions https://arxiv.org/pdf/1602.05149.pdf
[2] Wilson, Moriconi, Hutter, Deisenroth. The reparameterization trick for acquisition functions https://arxiv.org/pdf/1712.00424.pdf
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