Bayesian Optimization for Machine Learning : A Practical Guidebook
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Abstract (arXiv)
The engineering of machine learning systems is still a nascent field; relying on a seemingly daunting collection of quickly evolving tools and best practices. It is our hope that this guidebook will serve as a useful resource for machine learning practitioners looking to take advantage of Bayesian optimization techniques. We outline four example machine learning problems that can be solved using open source machine learning libraries, and highlight the benefits of using Bayesian optimization in the context of these common machine learning applications.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Dec 2016.
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Citing papers per year: 2022: 2; 2023: 2; 2024: 3; 2025: 3.
10 papers.
- 2022A Comparative study of Hyper-Parameter Optimization Toolscited by 10
- 2025TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Trackercited by 4
- 2023Mastering the exploration-exploitation trade-off in Bayesian Optimizationcited by 3
- 2022BERT-Based Combination of Convolutional and Recurrent Neural Network for Indonesian Sentiment Analysiscited by 1
- 2023Mithridates: Auditing and Boosting Backdoor Resistance of Machine Learning Pipelinescited by 1
- 2024A mechanism-driven reinforcement learning framework for shape optimization of airfoilscited by 0
- 2024Sentiment-driven prediction of financial returns: a Bayesian-enhanced FinBERT approachcited by 0
- 2024Structuring a Training Strategy to Robustify Perception Models with Realistic Image Augmentationscited by 0
- 2025HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedbackcited by 0
- 2025Sparse minimum Redundancy Maximum Relevance for feature selectioncited by 0
- 2025Sparse minimum Redundancy Maximum Relevance for feature selection26 Aug 2025
- 2025TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker26 Jun 2025
- 2025HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedback30 Jan 2025
- 2024Structuring a Training Strategy to Robustify Perception Models with Realistic Image Augmentations30 Aug 2024
- 2024Sentiment-driven prediction of financial returns: a Bayesian-enhanced FinBERT approach7 Mar 2024
- 2024A mechanism-driven reinforcement learning framework for shape optimization of airfoils7 Mar 2024
- 2023Mastering the exploration-exploitation trade-off in Bayesian Optimization15 May 2023
- 2023Mithridates: Auditing and Boosting Backdoor Resistance of Machine Learning Pipelines9 Feb 2023
- 2022BERT-Based Combination of Convolutional and Recurrent Neural Network for Indonesian Sentiment Analysis10 Nov 2022
- 2022A Comparative study of Hyper-Parameter Optimization Tools17 Jan 2022