mlsanityData to 14 Oct 2026

A warped kernel improving robustness in Bayesian optimization via random embeddings

arXiv 1411.3685 ↗First posted 13 Nov 2014math.OC stat.MLcited by 17

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Abstract (arXiv)

This works extends the Random Embedding Bayesian Optimization approach by integrating a warping of the high dimensional subspace within the covariance kernel. The proposed warping, that relies on elementary geometric considerations, allows mitigating the drawbacks of the high extrinsic dimensionality while avoiding the algorithm to evaluate points giving redundant information. It also alleviates constraints on bound selection for the embedded domain, thus improving the robustness, as illustrated with a test case with 25 variables and intrinsic dimension 6.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Nov 2014.

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Citing papers per year: 2021: 4; 2022: 4; 2023: 3; 2024: 3; 2025: 3.

17 papers.

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  1. 2021Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spacescited by 53
  2. 2023Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspacescited by 52
  3. 2022Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimizationcited by 37
  4. 2023Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spacescited by 28
  5. 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequencescited by 23
  6. 2023Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimizationcited by 9
  7. 2021Global optimization using random embeddingscited by 6
  8. 2021Sensitivity Prewarping for Local Surrogate Modelingcited by 4
  9. 2022Learning Representation for Bayesian Optimization with Collision-free Regularizationcited by 3
  10. 2024Expected Coordinate Improvement for High-Dimensional Bayesian Optimizationcited by 2
  11. 2022A model aggregation approach for high-dimensional large-scale optimizationcited by 1
  12. 2022Linear Embedding-based High-dimensional Batch Bayesian Optimization without Reconstruction Mappingscited by 1
5 more
  1. 2024High dimensional Bayesian Optimization via Condensing-Expansion Projectioncited by 1
  2. 2021Scaling Bayesian Optimization With Game Theorycited by 0
  3. 2025Selecting Critical Scenarios of DER Adoption in Distribution Grids Using Bayesian Optimizationcited by 0
  4. 2025An Adaptive Dropout Approach for High-Dimensional Bayesian Optimizationcited by 0
  5. 2025Nonlinear Dimensionality Reduction Techniques for Bayesian Optimizationcited by 0