mlsanityData to 7 Oct 2026

Bayesian Optimisation over Multiple Continuous and Categorical Inputs

arXiv 1906.08878 ↗First posted 20 Jun 2019stat.ML cs.LGcited by 55

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Abstract (arXiv)

Efficient optimisation of black-box problems that comprise both continuous and categorical inputs is important, yet poses significant challenges. We propose a new approach, Continuous and Categorical Bayesian Optimisation (CoCaBO), which combines the strengths of multi-armed bandits and Bayesian optimisation to select values for both categorical and continuous inputs. We model this mixed-type space using a Gaussian Process kernel, designed to allow sharing of information across multiple categorical variables, each with multiple possible values; this allows CoCaBO to leverage all available data efficiently. We extend our method to the batch setting and propose an efficient selection procedure that dynamically balances exploration and exploitation whilst encouraging batch diversity. We demonstrate empirically that our method outperforms existing approaches on both synthetic and real-world optimisation tasks with continuous and categorical inputs.

Key facts. Cited by 55 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jun 2019.

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Citing papers per year: 2021: 11; 2022: 12; 2023: 7; 2024: 8; 2025: 11; 2026: 6.

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  1. 2022Recent Advances in Bayesian Optimizationcited by 74
  2. 2021Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spacescited by 51
  3. 2021Revisiting Design Choices in Offline Model-Based Reinforcement Learningcited by 50
  4. 2021GIBBON: General-purpose Information-Based Bayesian OptimisatioNcited by 47
  5. 2022Joint Entropy Search for Multi-objective Bayesian Optimizationcited by 45
  6. 2022Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterizationcited by 35
  7. 2023Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spacescited by 27
  8. 2023Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddingscited by 24
  9. 2021Bayesian Optimization over Hybrid Spacescited by 23
  10. 2021Counterfactual Explanations for Arbitrary Regression Modelscited by 22
  11. 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequencescited by 22
  12. 2022Distributionally Robust Bayesian Optimization with varphi-divergencescited by 16
38 more
  1. 2023Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimizationcited by 15
  2. 2024Bayesian optimization as a flexible and efficient design framework for sustainable process systemscited by 15
  3. 2022Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spacescited by 14
  4. 2021Automated Deep Learning: Neural Architecture Search Is Not the Endcited by 13
  5. 2023Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlowcited by 11
  6. 2021EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functionscited by 9
  7. 2022c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimizationcited by 9
  8. 2021Non-smooth Bayesian Optimization in Tuning Problemscited by 8
  9. 2023SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spacescited by 7
  10. 2021DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecturecited by 6
  11. 2022Bayesian Optimization For Multi-Objective Mixed-Variable Problemscited by 5
  12. 2026AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuningcited by 5
  13. 2021Mixed Variable Bayesian Optimization with Frequency Modulated Kernelscited by 4
  14. 2022Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimizationcited by 4
  15. 2024CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimizationcited by 4
  16. 2022B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Searchcited by 3
  17. 2023Mastering the exploration-exploitation trade-off in Bayesian Optimizationcited by 3
  18. 2024A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Liftingcited by 3
  19. 2025Wasserstein Distributionally Robust Bayesian Optimization with Continuous Contextcited by 3
  20. 2025The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learningcited by 3
  21. 2021Explaining Inference Queries with Bayesian Optimizationcited by 2
  22. 2024CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimizationcited by 2
  23. 2025BARK: A Fully Bayesian Tree Kernel for Black-box Optimizationcited by 2
  24. 2025Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimizationcited by 2
  25. 2022Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lenscited by 1
  26. 2024Bayesian Optimization of Functions over Node Subsets in Graphscited by 1
  27. 2025BO-SA-PINNs: Self-adaptive physics-informed neural networks based on Bayesian optimization for automatically designing PDE solverscited by 1
  28. 2025A Guide to Bayesian Optimization in Bioprocess Engineeringcited by 1
  29. 2025Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimizationcited by 1
  30. 2022Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spacescited by 0
  31. 2022Bayesian Optimisation for Mixed-Variable Inputs using Value Proposalscited by 0
  32. 2023Global and Preference-based Optimization with Mixed Variables using Piecewise Affine Surrogatescited by 0
  33. 2024A Unified Gaussian Process for Branching and Nested Hyperparameter Optimizationcited by 0
  34. 2024Learning Rate-Free Reinforcement Learning: A Case for Model Selection with Non-Stationary Objectivescited by 0
  35. 2025CatBOX: A Categorical-Continuous Bayesian Optimization with Spectral Mixture Kernels for Accelerated Catalysis Experimentscited by 0
  36. 2025MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioningcited by 0
  37. 2025DT-PBO: an Interpretable Tree-based Surrogate Model for Preferential Bayesian Optimizationcited by 0
  38. 2025BayesSum: Bayesian Quadrature in Discrete Spacescited by 0

50 most cited of 55 All 55 (JSON)