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Question: SEBO optimization with parameter dependency | logistic parameter constrains #2174
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So what you're looking at is a hierarchical search space. We have some (basic) support for this ( Lines 515 to 516 in fcc5178
Line 437 in fcc5178
@saitcakmak, @dme65 do you have a sense of this? |
I don't know how well HSS would interact with SEBO for this use case. Under the hood, the acquisition function will be optimized in the flattened space without fixing the values of x2 & x3, so these will be included in the sparsity computations as well. Since the conditional structure here is super simple, you could try a manual approach here. Let Ax generate a candidate with all three parameters optimized and compare the acquisition value of this candidate to x1=x2=x3=0. You can then evaluate the one that performs better. But this would not scale too well beyond a few parameters. You could also do similar things using the Fixed features: https://github.com/facebook/Ax/blob/main/ax/modelbridge/base.py#L753-L755 |
Assuming the Your best bet is probably to find a way to optimize the acquisition function for each path in the hierarchical search space structure and then pick the best (this is what @saitcakmak suggested above). One thing to watch out for in that setting is that you may end up with x1=0 but not x2=x3=0 in the case where you optimize all parameters. |
@dme65 @saitcakmak @Balandat Thank you so much for your helpful inputs. When I use SEBO to optimize all parameters, it works well for most of the time and sometimes may have results with x1 = 0 but not x2 = x3 = 0. (main issue remaining for my problem) I will try to study more on this. |
I am using SEBO to identify the main control parameters of my problem. some of the control parameters have dependencies. that said, when parameter x1 is off the value of x2 and x3 no longer impact my outcome. thus I would like specify certain parameter constraints to hopefully reduce search space and speed up optimizaton: if x1 is selected to be 0, then set x2 = x3 = 0. else if x1 >0 search x2 x3 in their search bound. Can I reach this goal with current Ax /SEBO functionality? if not, is there an easy way to enable this ?
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