mlsanityData to 13 Oct 2026

Scalable Constrained Bayesian Optimization

arXiv 2002.08526 ↗First posted 20 Feb 2020cs.LG cs.AI stat.MLcited by 84

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Abstract (arXiv)

The global optimization of a high-dimensional black-box function under black-box constraints is a pervasive task in machine learning, control, and engineering. These problems are challenging since the feasible set is typically non-convex and hard to find, in addition to the curses of dimensionality and the heterogeneity of the underlying functions. In particular, these characteristics dramatically impact the performance of Bayesian optimization methods, that otherwise have become the de facto standard for sample-efficient optimization in unconstrained settings, leaving practitioners with evolutionary strategies or heuristics. We propose the scalable constrained Bayesian optimization (SCBO) algorithm that overcomes the above challenges and pushes the applicability of Bayesian optimization far beyond the state-of-the-art. A comprehensive experimental evaluation demonstrates that SCBO achieves excellent results on a variety of benchmarks. To this end, we propose two new control problems that we expect to be of independent value for the scientific community.

Key facts. Cited by 84 papers in the map (data through 13 Oct 2026). First posted on arXiv 20 Feb 2020.

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Citing papers per year: 2021: 13; 2022: 5; 2023: 19; 2024: 12; 2025: 19; 2026: 16.

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  1. 2021Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020cited by 147
  2. 2023Unexpected Improvements to Expected Improvement for Bayesian Optimizationcited by 145
  3. 2021High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspacescited by 140
  4. 2021Multi-Objective Bayesian Optimization over High-Dimensional Search Spacescited by 87
  5. 2023Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspacescited by 51
  6. 2021OpenBox: A Generalized Black-box Optimization Servicecited by 46
  7. 2022Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterizationcited by 35
  8. 2021Bayesian Optimization with High-Dimensional Outputscited by 32
  9. 2022Discovering Many Diverse Solutions with Bayesian Optimizationcited by 30
  10. 2023Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spacescited by 27
  11. 2021Sequential- and Parallel- Constrained Max-value Entropy Search via Information Lower Boundcited by 23
  12. 2022On Kernelized Multi-Armed Bandits with Constraintscited by 23
38 more
  1. 2023The Behavior and Convergence of Local Bayesian Optimizationcited by 20
  2. 2023BOtied: Multi-objective Bayesian optimization with tied multivariate rankscited by 15
  3. 2025LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithmscited by 10
  4. 2021Bayesian Optimisation for Constrained Problemscited by 9
  5. 2021A portfolio approach to massively parallel Bayesian optimizationcited by 9
  6. 2022c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimizationcited by 9
  7. 2023OpenBox: A Python Toolkit for Generalized Black-box Optimizationcited by 9
  8. 2024Scalable Bayesian Optimization via Focalized Sparse Gaussian Processescited by 8
  9. 2022Tuning Particle Accelerators with Safety Constraints using Bayesian Optimizationcited by 7
  10. 2021Optimizing High-Dimensional Physics Simulations via Composite Bayesian Optimizationcited by 6
  11. 2023No-Regret Constrained Bayesian Optimization of Noisy and Expensive Hybrid Models using Differentiable Quantile Function Approximationscited by 6
  12. 2023Constrained Causal Bayesian Optimizationcited by 6
  13. 2023Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approachcited by 6
  14. 2023Constrained Bayesian Optimization Under Partial Observations: Balanced Improvements and Provable Convergencecited by 6
  15. 2024High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategycited by 6
  16. 2024Boundary Exploration for Bayesian Optimization With Unknown Physical Constraintscited by 6
  17. 2024Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimationcited by 6
  18. 2021Failure-averse Active Learning for Physics-constrained Systemscited by 5
  19. 2023Joint Composite Latent Space Bayesian Optimizationcited by 5
  20. 2024Voronoi Candidates for Bayesian Optimizationcited by 5
  21. 2026BayeSQP: Bayesian Optimization through Sequential Quadratic Programmingcited by 5
  22. 2026Agentic Bayesian Optimization through Surrogate-Augmented Autoresearchcited by 5
  23. 2021Two-step Lookahead Bayesian Optimization with Inequality Constraintscited by 4
  24. 2023Black-Box Optimization with Implicit Constraints for Public Policycited by 4
  25. 2024Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systemscited by 4
  26. 2025On the convergence rate of noisy Bayesian Optimization with Expected Improvementcited by 4
  27. 2025Feasibility-Driven Trust Region Bayesian Optimizationcited by 4
  28. 2025Posterior Inference in Latent Space for Scalable Constrained Black-box Optimizationcited by 4
  29. 2021A sampling criterion for constrained Bayesian optimization with uncertaintiescited by 3
  30. 2024A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Liftingcited by 3
  31. 2025BILBO: BILevel Bayesian Optimizationcited by 3
  32. 2023Scalable Bayesian optimization with high-dimensional outputs using randomized prior networkscited by 2
  33. 2023Constrained Bayesian Optimization with Adaptive Active Learning of Unknown Constraintscited by 2
  34. 2024Optimal Initialization of Batch Bayesian Optimizationcited by 2
  35. 2024Pure Exploration for Constrained Best Mixed Arm Identification with a Fixed Budgetcited by 2
  36. 2025Constrained multi-fidelity Bayesian optimization with automatic stop conditioncited by 2
  37. 2025CoTune: Co-evolutionary Configuration Tuningcited by 2
  38. 2026On Regret Bounds of Thompson Sampling for Bayesian Optimizationcited by 2

50 most cited of 84 All 84 (JSON)