Optuna Constrained Tree-Structured Parzen Estimator Is a Joint Density Generalization of c-TPE
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Computer Science > Machine Learning
Title:Optuna Constrained Tree-Structured Parzen Estimator Is a Joint Density Generalization of c-TPE
Abstract:Constrained hyperparameter optimization (HPO) is common in practice, yet Optuna's widely used constrained TPE lacks algorithmic analysis. While c-TPE proposes an expected constrained improvement (ECI) approach assuming independence between the objective and constraints, Optuna uses a single joint density over both. We show that Optuna's constrained TPE is joint c-TPE -- the same ECI acquisition function using a joint likelihood. We demonstrate joint c-TPE is invariant to constraint duplication whereas independent c-TPE degrades as the product accumulates duplicated factors. We outline practical tradeoffs between the formulations and directions for future study.
| Subjects: | Machine Learning (cs.LG) |
| Cite as: | arXiv:2606.09889 [cs.LG] |
| (or arXiv:2606.09889v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2606.09889
arXiv-issued DOI via DataCite
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