mlsanityData to 14 Oct 2026

High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

arXiv 1802.07028 ↗First posted 20 Feb 2018cs.LG stat.MLcited by 59

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Abstract (arXiv)

Bayesian optimization (BO) is a popular technique for sequential black-box function optimization, with applications including parameter tuning, robotics, environmental monitoring, and more. One of the most important challenges in BO is the development of algorithms that scale to high dimensions, which remains a key open problem despite recent progress. In this paper, we consider the approach of Kandasamy et al. (2015), in which the high-dimensional function decomposes as a sum of lower-dimensional functions on subsets of the underlying variables. In particular, we significantly generalize this approach by lifting the assumption that the subsets are disjoint, and consider additive models with arbitrary overlap among the subsets. By representing the dependencies via a graph, we deduce an efficient message passing algorithm for optimizing the acquisition function. In addition, we provide an algorithm for learning the graph from samples based on Gibbs sampling. We empirically demonstrate the effectiveness of our methods on both synthetic and real-world data.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Feb 2018.

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Citing papers per year: 2021: 11; 2022: 9; 2023: 8; 2024: 13; 2025: 11; 2026: 7.

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  1. 2024Vanilla Bayesian Optimization Performs Great in High Dimensionscited by 92
  2. 2022Recent Advances in Bayesian Optimizationcited by 76
  3. 2021Pre-trained Gaussian Processes for Bayesian Optimizationcited by 63
  4. 2021Gaussian Process Bandit Optimization with Few Batchescited by 57
  5. 2021Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spacescited by 53
  6. 2022Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimizationcited by 37
  7. 2023Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?cited by 36
  8. 2024Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimizationcited by 34
  9. 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequencescited by 23
  10. 2021Parallelizing Thompson Samplingcited by 20
  11. 2025Posterior Inference with Diffusion Models for High-dimensional Black-box Optimizationcited by 13
  12. 2021Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selectioncited by 12
38 more
  1. 2025We Still Don't Understand High-Dimensional Bayesian Optimizationcited by 12
  2. 2024Functional Graphical Models: Structure Enables Offline Data-Driven Optimizationcited by 11
  3. 2022Graph Neural Network Banditscited by 10
  4. 2024"Noisier" Noise Contrastive Eestimation is (Almost) Maximum Likelihoodcited by 8
  5. 2021Stochastic Gradient Line Bayesian Optimization for Efficient Noise-Robust Optimization of Parameterized Quantum Circuitscited by 7
  6. 2022High Dimensional Bayesian Optimization with Kernel Principal Component Analysiscited by 7
  7. 2023Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learningcited by 6
  8. 2021Adversarial Attacks on Gaussian Process Banditscited by 5
  9. 2022MBORE: Multi-objective Bayesian Optimisation by Density-Ratio Estimationcited by 5
  10. 2023Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimizationcited by 5
  11. 2025High Dimensional Bayesian Optimization using Lasso Variable Selectioncited by 4
  12. 2024Active Learning for Level Set Estimation Using Randomized Straddle Algorithmscited by 3
  13. 2024Cliqueformer: Model-Based Optimization with Structured Transformerscited by 3
  14. 2021Bayesian Optimization with Clustering and Rollback for CNN Auto Pruningcited by 2
  15. 2022Test and Evaluation of Quadrupedal Walking Gaits through Sim2Real Gap Quantificationcited by 2
  16. 2022Bayesian Optimization with Informative Covariancecited by 2
  17. 2024Expected Coordinate Improvement for High-Dimensional Bayesian Optimizationcited by 2
  18. 2024High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspacescited by 2
  19. 2025Enhancing Trust-Region Bayesian Optimization via Newton Methodscited by 2
  20. 2025BO4Mob: Bayesian Optimization Benchmarks for High-Dimensional Urban Mobility Problemcited by 2
  21. 2024Combining additivity and active subspaces for high-dimensional Gaussian process modelingcited by 1
  22. 2026High-dimensional Level Set Estimation with Trust Regions and Double Acquisition Functionscited by 1
  23. 2021Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modelingcited by 0
  24. 2021High-Dimensional Simulation Optimization via Brownian Fields and Sparse Gridscited by 0
  25. 2021Scaling Bayesian Optimization With Game Theorycited by 0
  26. 2022High-Dimensional Bayesian Optimization with Constraints: Application to Powder Weighingcited by 0
  27. 2022Monte Carlo Tree Descent for Black-Box Optimizationcited by 0
  28. 2023Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimizationcited by 0
  29. 2023Representing Additive Gaussian Processes by Sparse Matricescited by 0
  30. 2023Learning Relevant Contextual Variables Within Bayesian Optimizationcited by 0
  31. 2023Dependency Structure Search Bayesian Optimization for Decision Making Modelscited by 0
  32. 2023Multi-Agent Bayesian Optimization with Coupled Black-Box and Affine Constraintscited by 0
  33. 2024Bayesian Optimization that Limits Search Region to Lower Dimensions Utilizing Local GPRcited by 0
  34. 2024Safe Bayesian Optimization for Complex Control Systems via Additive Gaussian Processescited by 0
  35. 2024Swine Diet Design using Multi-objective Regionalized Bayesian Optimizationcited by 0
  36. 2025Sparse Nonparametric Contextual Banditscited by 0
  37. 2025An Adaptive Dropout Approach for High-Dimensional Bayesian Optimizationcited by 0
  38. 2025Learning Low-Dimensional Embeddings for Black-Box Optimizationcited by 0

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