Have you any thoughts on an additional option for different optimization routines when calling acq_max?
My thought was something like this:
def acq_max(ac, gp, y_max, bounds, random_state, n_warmup=10000, n_iter=10, optimization_routine="L-BFGS-B"):
:optimization_routine str optional(default="L-BFGS-B"): The algorithm used for finding the maximum of the acquisition function
Possible options are:
"L-BFGS-B"
"Nelder-Mead"
...
"differential-evolution"
"basinhopping"
Then later on in the function have a case depending on the argument's value. My thought is options like differential-evolution won't need the random restarts, and might perform better.
I can work on this, just wanted to shoot it past you all.
Hi @osullivryan , yes that sounds like a great idea. Given how time constraint I've been these days I won't be able to work on this feature anytime soon, but PRs are more than appreciated =)
Hello BayesianOptimization team,
Have you any thoughts on an additional option for different optimization routines when calling
acq_max
?My thought was something like this:
Then later on in the function have a case depending on the argument's value. My thought is options like
differential-evolution
won't need the random restarts, and might perform better.I can work on this, just wanted to shoot it past you all.
Ryan