Sam Daulton
Sam Daulton
Hmm it kind of looks like Ax is minimizing both objectives in the later iterations. What are the inferred objective thresholds? Do these seem reasonable. What does the cross validation...
We have some improved methods in the works for better treatment of integer parameters (in the next couple weeks), which should resolve this issue. cc: @Balandat
+1. It would be great to get to get some more clarity on the issue here. Using jit should greatly speed things up
Thanks for putting this up @saitcakmak! I think there are very few situations where using `sample_around_best` would perform worse. It is worth noting that `sample_around_best` does not replace the space...
@saitcakmak What is the status of this PR? It would great to get his merged in
This issue in #480 is more related to equality constraints with transformed parameters, right? Subsetting is already supported (as long as you know what the subset(s) are that you want...
Has this been resolved? My hunch is that that the PF is nearly converged and the model believes that the greatest potential improvements in hypervolume will come from the left...
I echo what @eytan mentioned about reducing the number of objectives. To speed things up, you can reduce the number of MC samples used to approximate the expectation over the...
Appendix F.4 of https://arxiv.org/pdf/2006.05078.pdf includes some discussion. Random scalarizations are common for >5 objectives. Approximate box decompositions can be helpful for 4-5 objectives