mlsanityData to 7 Oct 2026

Practical Transfer Learning for Bayesian Optimization

arXiv 1802.02219 ↗First posted 6 Feb 2018stat.ML cs.AIcited by 26

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Abstract (arXiv)

When hyperparameter optimization of a machine learning algorithm is repeated for multiple datasets it is possible to transfer knowledge to an optimization run on a new dataset. We develop a new hyperparameter-free ensemble model for Bayesian optimization that is a generalization of two existing transfer learning extensions to Bayesian optimization and establish a worst-case bound compared to vanilla Bayesian optimization. Using a large collection of hyperparameter optimization benchmark problems, we demonstrate that our contributions substantially reduce optimization time compared to standard Gaussian process-based Bayesian optimization and improve over the current state-of-the-art for transfer hyperparameter optimization.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Feb 2018.

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Citing papers per year: 2021: 3; 2022: 3; 2023: 9; 2024: 0; 2025: 5; 2026: 6.

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  1. 2023PFNs4BO: In-Context Learning for Bayesian Optimizationcited by 70
  2. 2022πBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimizationcited by 69
  3. 2021Pre-trained Gaussian Processes for Bayesian Optimizationcited by 63
  4. 2021YAHPO Gym -- An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimizationcited by 61
  5. 2025QuestBench: Can LLMs ask the right question to acquire information in reasoning tasks?cited by 56
  6. 2023PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learningcited by 31
  7. 2023Transfer Learning for Bayesian Optimization: A Surveycited by 27
  8. 2023A General Framework for User-Guided Bayesian Optimizationcited by 22
  9. 2021Triangulation candidates for Bayesian optimizationcited by 11
  10. 2022Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimatorcited by 7
  11. 2022HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimizationcited by 4
  12. 2025None To Optima in Few Shots: Bayesian Optimization with MDP Priorscited by 3
14 more
  1. 2023MALIBO: Meta-learning for Likelihood-free Bayesian Optimizationcited by 2
  2. 2023Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasetscited by 2
  3. 2025Dynamic Priors in Bayesian Optimization for Hyperparameter Optimizationcited by 2
  4. 2023Federated Covariate Shift Adaptation for Missing Target Output Valuescited by 1
  5. 2023Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisationcited by 1
  6. 2025Derivation of Output Correlation Inferences for Multi-Output (aka Multi-Task) Gaussian Processcited by 1
  7. 2025Provable Accelerated Bayesian Optimization with Knowledge Transfercited by 1
  8. 2023Karasu: A Collaborative Approach to Efficient Cluster Configuration for Big Data Analyticscited by 0
  9. 2026SMOG: Scalable Meta-Learning for Multi-Objective Bayesian Optimizationcited by 0
  10. 2026Weighted Wasserstein Barycenter of Gaussian Processes for exotic Bayesian Optimization taskscited by 0
  11. 2026Empirical Gaussian Processescited by 0
  12. 2026Transfer Learning in Bayesian Optimization for Aircraft Designcited by 0
  13. 2026Regime-Conditioned Evaluation in Multi-Context Bayesian Optimizationcited by 0
  14. 2026Oracle Supervision Transfers for Hyperparameter Prediction in Model-Based Image Denoisingcited by 0