No-Regret Bayesian Optimization with Unknown Hyperparameters

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No-Regret Bayesian Optimization with Unknown Hyperparameters

10 January 2019

Felix Berkenkamp

Angela P. Schoellig

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Papers citing "No-Regret Bayesian Optimization with Unknown Hyperparameters"

19 / 19 papers shown

Title
Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization Shogo Iwazaki GP 53 0 0 02 Jun 2025
Reliable algorithm selection for machine learning-guided design Clara Fannjiang Ji Won Park 95 0 0 26 Mar 2025
Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants Fares Fourati Salma Kharrat Vaneet Aggarwal Mohamed-Slim Alouini 116 0 0 06 Feb 2025
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal Juliusz Ziomek Masaki Adachi Michael A. Osborne 93 1 0 14 Oct 2024
Batch Bayesian Optimization for Replicable Experimental Design Zhongxiang Dai Q. Nguyen Sebastian Shenghong Tay Daisuke Urano Richalynn Leong Bryan Kian Hsiang Low Patrick Jaillet 42 5 0 02 Nov 2023
Self-Correcting Bayesian Optimization through Bayesian Active Learning Carl Hvarfner E. Hellsten Frank Hutter Luigi Nardi GP 90 16 0 21 Apr 2023
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization Shouri Hu Haowei Wang Zhongxiang Dai K. H. Low Szu Hui Ng 65 4 0 10 May 2022
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization Johannes Kirschner Mojmír Mutný Andreas Krause J. C. D. Portugal N. Hiller J. Snuverink 37 12 0 26 Mar 2022
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization Hung The Tran Sunil R. Gupta Santu Rana Svetha Venkatesh 50 14 0 15 Mar 2022
Meta-Learning Hypothesis Spaces for Sequential Decision-making Parnian Kassraie Jonas Rothfuss Andreas Krause OffRL 107 6 0 01 Feb 2022
Misspecified Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause 86 45 0 09 Nov 2021
Pre-trained Gaussian processes for Bayesian optimization Zehao Wang George E. Dahl Kevin Swersky Chansoo Lee Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 151 46 0 16 Sep 2021
Green Machine Learning via Augmented Gaussian Processes and Multi-Information Source Optimization Antonio Candelieri R. Perego Francesco Archetti 47 19 0 25 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 130 85 0 15 Jun 2020
Reward Design for Driver Repositioning Using Multi-Agent Reinforcement Learning Zhenyu Shou Xuan Di 83 57 0 17 Feb 2020
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness George Wynne F. Briol Mark Girolami 85 56 0 29 Jan 2020
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees Maria-Florina Balcan Tuomas Sandholm Ellen Vitercik 70 16 0 26 May 2019
Sampling Acquisition Functions for Batch Bayesian Optimization Alessandro De Palma Celestine Mendler-Dünner Thomas Parnell Andreea Anghel H. Pozidis 56 13 0 22 Mar 2019
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting A. Krishnamurthy John Langford Aleksandrs Slivkins Chicheng Zhang OffRL 175 65 0 05 Feb 2019