Comments (2)
As you said, the standard parameter constraints do not support complex nonlinear constraints. This is for a few reasons, not least that this makes the acquisition function optimization a lot more challenging. It also makes it a lot harder to deal with the parameter transformations that Ax applies under the hood. See #1797 (comment) for a more detailed discussion.
What is the mathematical problem you're trying to solve? Is there a way to express the constraints in other coordinates?
from ax.
Hi Balandat,
Thanks for your response and the discussion at #1797 is well understood. Then do you have any suggestion to address my issue? the mathematical problem I need to solve is that I only want to confine the SearchSpace
which only satisfy discriminant = b**2 - (4 * a * c) >= 0
requirement. Since otherwise, the sample from the SearchSpace
passed to a next step and they won't work, meaning the entire BO process stopped since the next step yields empty result. The next step only work once real solution exists, i.e. discriminant = b**2 - (4 * a * c) >= 0
. I have thinking about including 'discriminant' together with other parameters, x00, x01, x02, x03, x04 and x05
at SearchSpace
but it hasn't worked since there is no correlation between 'discriminant' and others. If you have any idea to resolve this or even discarding/abandon a sample which are not satisfy the criteria discriminant = b**2 - (4 * a * c) >= 0
, please let me know!
from ax.
Related Issues (20)
- `StandardizeY` transform requires non-empty data." when using SAASBO
- Plotting outside of a notebook HOT 1
- Setting search space step size in Ax Service API HOT 10
- Problem when Sobol falls back to HitAndRunPolytopeSampler HOT 5
- Arms from previous batch keep appearing in new batches HOT 5
- EHVI & NEHVI break with more than 7 objectives HOT 4
- Multi-objective experiments generate duplicated data HOT 5
- Question: Transforming objective when passing `best_f` to `ProbabilityOfImprovement`, etc. HOT 4
- [Question] Multiobjective optimization where one target has no optimization direction (but required range)
- How to expose the default acquisition function being used by AxClient() HOT 3
- Fix core docs related to linear constraints HOT 3
- Improve string normalization for constraint string parsing
- Replacement for `Models.GPKG` HOT 2
- Ax serice API for GPU
- Looking for suggestions for the objectives data HOT 3
- batch of suggestions HOT 14
- MOO Tutorial potentially incorrect model HOT 2
- Constraints on FixedParameters are not allowed HOT 6
- RegistryBundle can't be imported HOT 7
- [Bug] Arguments passed to BoTorch optimize_acqf don't work (in an intuitive way) or don't make sense HOT 1
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from ax.