mlsanityData to 14 Oct 2026

Optimization, fast and slow: optimally switching between local and Bayesian optimization

arXiv 1805.08610 ↗First posted 22 May 2018stat.ML cs.LGcited by 22

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Abstract (arXiv)

We develop the first Bayesian Optimization algorithm, BLOSSOM, which selects between multiple alternative acquisition functions and traditional local optimization at each step. This is combined with a novel stopping condition based on expected regret. This pairing allows us to obtain the best characteristics of both local and Bayesian optimization, making efficient use of function evaluations while yielding superior convergence to the global minimum on a selection of optimization problems, and also halting optimization once a principled and intuitive stopping condition has been fulfilled.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 May 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 7; 2022: 2; 2023: 5; 2024: 1; 2025: 4; 2026: 3.

22 papers.

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  1. 2023Unexpected Improvements to Expected Improvement for Bayesian Optimizationcited by 149
  2. 2021Local policy search with Bayesian optimizationcited by 38
  3. 2022Local Bayesian optimization via maximizing probability of descentcited by 30
  4. 2021TREGO: a Trust-Region Framework for Efficient Global Optimizationcited by 29
  5. 2021Automatic Termination for Hyperparameter Optimizationcited by 21
  6. 2024Stopping Bayesian Optimization with Probabilistic Regret Boundscited by 11
  7. 2021Revisiting Bayesian Optimization in the light of the COCO benchmarkcited by 10
  8. 2025User Preference Meets Pareto-Optimality in Multi-Objective Bayesian Optimizationcited by 6
  9. 2021Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approachcited by 2
  10. 2022Bayesian Optimization with Informative Covariancecited by 2
  11. 2023LABCAT: Locally adaptive Bayesian optimization using principal-component-aligned trust regionscited by 2
  12. 2023Hyper-parameter Tuning for Adversarially Robust Modelscited by 1
10 more
  1. 2023HomOpt: A Homotopy-Based Hyperparameter Optimization Methodcited by 1
  2. 2025Bayesian autoregression to optimize temporal Mat'ern kernel Gaussian process hyperparameterscited by 1
  3. 2021CobBO: Coordinate Backoff Bayesian Optimization with Two-Stage Kernelscited by 0
  4. 2021Searching in the Forest for Local Bayesian Optimizationcited by 0
  5. 2023Dependency Structure Search Bayesian Optimization for Decision Making Modelscited by 0
  6. 2025Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functionscited by 0
  7. 2025Efficient Sliced Wasserstein Distance Computation via Adaptive Bayesian Optimizationcited by 0
  8. 2026LAGO: A Local-Global Optimization Framework Combining Trust Region Methods and Bayesian Optimizationcited by 0
  9. 2026Regret-Based (ε,δ)-optimal Stopping Criteria for Bayesian Optimizationcited by 0
  10. 2026GRAPE: Gradient Refinement and Progress-Aware Exploitation for Query-Efficient High-Dimensional Bayesian Optimizationcited by 0