mlsanityData to 7 Oct 2026

A General Framework for User-Guided Bayesian Optimization

arXiv 2311.14645 ↗First posted 24 Nov 2023cs.LG stat.MLcited by 22

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Abstract (arXiv)

The optimization of expensive-to-evaluate black-box functions is prevalent in various scientific disciplines. Bayesian optimization is an automatic, general and sample-efficient method to solve these problems with minimal knowledge of the underlying function dynamics. However, the ability of Bayesian optimization to incorporate prior knowledge or beliefs about the function at hand in order to accelerate the optimization is limited, which reduces its appeal for knowledgeable practitioners with tight budgets. To allow domain experts to customize the optimization routine, we propose ColaBO, the first Bayesian-principled framework for incorporating prior beliefs beyond the typical kernel structure, such as the likely location of the optimizer or the optimal value. The generality of ColaBO makes it applicable across different Monte Carlo acquisition functions and types of user beliefs. We empirically demonstrate ColaBO's ability to substantially accelerate optimization when the prior information is accurate, and to retain approximately default performance when it is misleading.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 37 of its 72 references that are in the map. First posted on arXiv 24 Nov 2023.

Builds on

37 of 72 references.

References · 37

  1. 2013Auto-Encoding Variational Bayescited by 3,980
  2. 2019Scalable Global Optimization via Local Bayesian Optimizationcited by 359
  3. 2021Transformers Can Do Bayesian Inferencecited by 338
  4. 2021SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimizationcited by 229
  5. 2018A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decaycited by 223
  6. 2017Max-value Entropy Search for Efficient Bayesian Optimizationcited by 202
  7. 2014Predictive Entropy Search for Efficient Global Optimization of Black-box Functionscited by 201
  8. 2019BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Searchcited by 175
  9. 2023Unexpected Improvements to Expected Improvement for Bayesian Optimizationcited by 144
  10. 2020Efficiently Sampling Functions from Gaussian Process Posteriorscited by 125
  11. 2017Batched Large-scale Bayesian Optimization in High-dimensional Spacescited by 116
  12. 2018Maximizing acquisition functions for Bayesian optimizationcited by 113
25 more
  1. 2017Constrained Bayesian Optimization with Noisy Experimentscited by 103
  2. 2020PACOH: Bayes-Optimal Meta-Learning with PAC-Guaranteescited by 85
  3. 2021Few-Shot Bayesian Optimization with Deep Kernel Surrogatescited by 70
  4. 2023PFNs4BO: In-Context Learning for Bayesian Optimizationcited by 70
  5. 2022πBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimizationcited by 69
  6. 2020Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDLcited by 67
  7. 2021Pre-trained Gaussian Processes for Bayesian Optimizationcited by 63
  8. 2018BOCK : Bayesian Optimization with Cylindrical Kernelscited by 62
  9. 2017The reparameterization trick for acquisition functionscited by 61
  10. 2022Joint Entropy Search for Maximally-Informed Bayesian Optimizationcited by 55
  11. 2015Predictive Entropy Search for Bayesian Optimization with Unknown Constraintscited by 51
  12. 2019Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learningcited by 50
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  14. 2022Joint Entropy Search for Multi-objective Bayesian Optimizationcited by 45
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  16. 2021Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Informationcited by 33
  17. 2021Bayesian Optimization of Function Networkscited by 33
  18. 2023PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learningcited by 31
  19. 2023Sampling from Gaussian Process Posteriors using Stochastic Gradient Descentcited by 27
  20. 2018Practical Transfer Learning for Bayesian Optimizationcited by 26
  21. 2021Sequential- and Parallel- Constrained Max-value Entropy Search via Information Lower Boundcited by 23
  22. 2021Meta-Learning Reliable Priors in the Function Spacecited by 23
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 10; 2026: 6.

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  1. 2024Position: A Call to Action for a Human-Centered AutoML Paradigmcited by 14
  2. 2025Language-Based Bayesian Optimization Research Assistant (BORA)cited by 13
  3. 2025Reasoning BO: Enhancing Bayesian Optimization with Long-Context Reasoning Power of LLMscited by 8
  4. 2025PABBO: Preferential Amortized Black-Box Optimizationcited by 7
  5. 2025Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddingscited by 6
  6. 2024Improving Hyperparameter Optimization with Checkpointed Model Weightscited by 5
  7. 2024Principled Bayesian Optimisation in Collaboration with Human Expertscited by 5
  8. 2024Optimizing Posterior Samples for Bayesian Optimization via Rootfindingcited by 5
  9. 2026Unleashing LLMs in Bayesian Optimization: Preference-Guided Framework for Scientific Discoverycited by 5
  10. 2025HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimizationcited by 4
  11. 2026LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentationcited by 4
  12. 2024CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimizationcited by 2
10 more
  1. 2025Dynamic Priors in Bayesian Optimization for Hyperparameter Optimizationcited by 2
  2. 2024Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimizationcited by 1
  3. 2025FigBO: A Generalized Acquisition Function Framework with Look-Ahead Capability for Bayesian Optimizationcited by 1
  4. 2025Natural Evolutionary Search meets Probabilistic Numericscited by 1
  5. 2026Human-in-the-Loop Meta Bayesian Optimization for Fusion Energy and Scientific Applicationscited by 1
  6. 2026Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputscited by 1
  7. 2025Counterfactual Credit Guided Bayesian Optimizationcited by 0
  8. 2025HiBBO: HiPPO-based Space Consistency for High-dimensional Bayesian Optimisationcited by 0
  9. 2026Elicitation-Augmented Bayesian Optimizationcited by 0
  10. 2026Harnessing Large Language Models to Compile Task-Relevant Context into Bayesian Optimisationcited by 0