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Bayesian Optimization with Unknown Constraints

arXiv 1403.5607 ↗First posted 22 Mar 2014stat.ML cs.LGcited by 109

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Abstract (arXiv)

Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective functions. Many real-world optimization problems of interest also have constraints which are unknown a priori. In this paper, we study Bayesian optimization for constrained problems in the general case that noise may be present in the constraint functions, and the objective and constraints may be evaluated independently. We provide motivating practical examples, and present a general framework to solve such problems. We demonstrate the effectiveness of our approach on optimizing the performance of online latent Dirichlet allocation subject to topic sparsity constraints, tuning a neural network given test-time memory constraints, and optimizing Hamiltonian Monte Carlo to achieve maximal effectiveness in a fixed time, subject to passing standard convergence diagnostics.

Key facts. Cited by 109 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Mar 2014.

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Citing papers per year: 2021: 18; 2022: 16; 2023: 22; 2024: 17; 2025: 17; 2026: 19.

109 papers.

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  1. 2023Unexpected Improvements to Expected Improvement for Bayesian Optimizationcited by 144
  2. 2021Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challengescited by 143
  3. 2021Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvementcited by 115
  4. 2022Joint Entropy Search for Multi-objective Bayesian Optimizationcited by 45
  5. 2023Mirror Diffusion Models for Constrained and Watermarked Generationcited by 38
  6. 2021Bayesian Optimization with High-Dimensional Outputscited by 32
  7. 2021Data-Driven Offline Optimization For Architecting Hardware Acceleratorscited by 29
  8. 2021GoSafe: Globally Optimal Safe Robot Learningcited by 27
  9. 2023Looping in the Human Collaborative and Explainable Bayesian Optimizationcited by 27
  10. 2021Sequential- and Parallel- Constrained Max-value Entropy Search via Information Lower Boundcited by 23
  11. 2022On Kernelized Multi-Armed Bandits with Constraintscited by 23
  12. 2022Multi-Fidelity Cost-Aware Bayesian Optimizationcited by 20
38 more
  1. 2021A Full-Stack Search Technique for Domain Optimized Deep Learning Acceleratorscited by 19
  2. 2021Promoting Fairness through Hyperparameter Optimizationcited by 17
  3. 2022GoSafeOpt: Scalable Safe Exploration for Global Optimization of Dynamical Systemscited by 17
  4. 2021An Efficient Batch Constrained Bayesian Optimization Approach for Analog Circuit Synthesis via Multi-objective Acquisition Ensemblecited by 13
  5. 2025TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning for Discrete Diffusioncited by 13
  6. 2022Bayesian optimization with known experimental and design constraints for chemistry applicationscited by 11
  7. 2022Interactively Learning Preference Constraints in Linear Banditscited by 11
  8. 2021VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraintscited by 10
  9. 2023Bayesian Optimization with Formal Safety Guarantees via Online Conformal Predictioncited by 10
  10. 2022c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimizationcited by 9
  11. 2022Information-Theoretic Safe Exploration with Gaussian Processescited by 9
  12. 2024Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimizationcited by 9
  13. 2021Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturingcited by 8
  14. 2022PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence designcited by 8
  15. 2023Tuning Legged Locomotion Controllers via Safe Bayesian Optimizationcited by 8
  16. 2023Constrained Causal Bayesian Optimizationcited by 6
  17. 2023Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approachcited by 6
  18. 2023Constrained Bayesian Optimization Under Partial Observations: Balanced Improvements and Provable Convergencecited by 6
  19. 2024Boundary Exploration for Bayesian Optimization With Unknown Physical Constraintscited by 6
  20. 2024Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimationcited by 6
  21. 2021Failure-averse Active Learning for Physics-constrained Systemscited by 5
  22. 2021ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicinecited by 5
  23. 2022Bayesian Optimization Meets Hybrid Zero Dynamics: Safe Parameter Learning for Bipedal Locomotion Controlcited by 5
  24. 2022PF2ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimizationcited by 5
  25. 2023Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraintscited by 5
  26. 2024Principled Bayesian Optimisation in Collaboration with Human Expertscited by 5
  27. 2026BayeSQP: Bayesian Optimization through Sequential Quadratic Programmingcited by 5
  28. 2026Agentic Bayesian Optimization through Surrogate-Augmented Autoresearchcited by 5
  29. 2021Two-step Lookahead Bayesian Optimization with Inequality Constraintscited by 4
  30. 2022Towards Fairness-Aware Multi-Objective Optimizationcited by 4
  31. 2023Quantum approximate optimization via learning-based adaptive optimizationcited by 4
  32. 2023Black-Box Optimization with Implicit Constraints for Public Policycited by 4
  33. 2024Robust Entropy Search for Safe Efficient Bayesian Optimizationcited by 4
  34. 2024Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systemscited by 4
  35. 2025Active Learning with Selective Time-Step Acquisition for PDEscited by 4
  36. 2022CONFIG: Constrained Efficient Global Optimization for Closed-Loop Control System Optimization with Unmodeled Constraintscited by 3
  37. 2022Mind the Gap: Measuring Generalization Performance Across Multiple Objectivescited by 3
  38. 2023Rover: An online Spark SQL tuning service via generalized transfer learningcited by 3

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