mlsanityData to 7 Oct 2026

High Dimensional Bayesian Optimization Using Dropout

arXiv 1802.05400 ↗First posted 15 Feb 2018stat.MLcited by 40

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Abstract (arXiv)

Scaling Bayesian optimization to high dimensions is challenging task as the global optimization of high-dimensional acquisition function can be expensive and often infeasible. Existing methods depend either on limited active variables or the additive form of the objective function. We propose a new method for high-dimensional Bayesian optimization, that uses a dropout strategy to optimize only a subset of variables at each iteration. We derive theoretical bounds for the regret and show how it can inform the derivation of our algorithm. We demonstrate the efficacy of our algorithms for optimization on two benchmark functions and two real-world applications- training cascade classifiers and optimizing alloy composition.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Feb 2018.

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Citing papers per year: 2021: 7; 2022: 6; 2023: 8; 2024: 12; 2025: 4; 2026: 3.

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  1. 2021High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspacescited by 139
  2. 2024Vanilla Bayesian Optimization Performs Great in High Dimensionscited by 87
  3. 2021High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learningcited by 54
  4. 2022Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimizationcited by 37
  5. 2023Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?cited by 35
  6. 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequencescited by 22
  7. 2023B2Opt: Learning to Optimize Black-box Optimization with Little Budgetcited by 15
  8. 2022Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization (ZoMBI)cited by 14
  9. 2024Improving sample efficiency of high dimensional Bayesian optimization with MCMCcited by 9
  10. 2025We Still Don't Understand High-Dimensional Bayesian Optimizationcited by 9
  11. 2021Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturingcited by 8
  12. 2023Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimizationcited by 8
28 more
  1. 2021A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Modelscited by 7
  2. 2022High Dimensional Bayesian Optimization with Kernel Principal Component Analysiscited by 7
  3. 2023Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimizationcited by 5
  4. 2024BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddingscited by 4
  5. 2024Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systemscited by 4
  6. 2023A Bayesian Optimization approach for calibrating large-scale activity-based transport modelscited by 3
  7. 2025High Dimensional Bayesian Optimization using Lasso Variable Selectioncited by 3
  8. 2021High dimensional Bayesian Optimization Algorithm for Complex System in Time Seriescited by 2
  9. 2024Expected Coordinate Improvement for High-Dimensional Bayesian Optimizationcited by 2
  10. 2024Navigating in High-Dimensional Search Space: A Hierarchical Bayesian Optimization Approachcited by 2
  11. 2024High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspacescited by 2
  12. 2025Enhancing Trust-Region Bayesian Optimization via Newton Methodscited by 2
  13. 2026A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Searchcited by 2
  14. 2021Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputerscited by 1
  15. 2022High-dimensional Bayesian Optimization Algorithm with Recurrent Neural Network for Disease Control Models in Time Seriescited by 1
  16. 2022A model aggregation approach for high-dimensional large-scale optimizationcited by 1
  17. 2023Decreasing the Computing Time of Bayesian Optimization using Generalizable Memory Pruningcited by 1
  18. 2024An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimizationcited by 1
  19. 2024High dimensional Bayesian Optimization via Condensing-Expansion Projectioncited by 1
  20. 2026Extending Multi-Source Bayesian Optimization With Causality Principlescited by 1
  21. 2021CobBO: Coordinate Backoff Bayesian Optimization with Two-Stage Kernelscited by 0
  22. 2022High-Dimensional Bayesian Optimization with Constraints: Application to Powder Weighingcited by 0
  23. 2023Learning Relevant Contextual Variables Within Bayesian Optimizationcited by 0
  24. 2023Ambulance Demand Prediction via Convolutional Neural Networkscited by 0
  25. 2024Cost-Effective Methodology for Complex Tuning Searches in HPC: Navigating Interdependencies and Dimensionalitycited by 0
  26. 2024Bayesian Optimization that Limits Search Region to Lower Dimensions Utilizing Local GPRcited by 0
  27. 2025An Adaptive Dropout Approach for High-Dimensional Bayesian Optimizationcited by 0
  28. 2026Agentic High-Dimensional Bayesian Optimization with Hypothesis- and Evidence-Guided Searchcited by 0