Recent Advances in Bayesian Optimization

7 June 2022

Markus Olhofer

Papers citing "Recent Advances in Bayesian Optimization"

40 / 40 papers shown

Title
crowd-hpo: Realistic Hyperparameter Optimization and Benchmarking for Learning from Crowds with Noisy Labels M. Herde Lukas Lührs Denis Huseljic Bernhard Sick 22 0 0 12 Apr 2025
A Balanced Approach of Rapid Genetic Exploration and Surrogate Exploitation for Hyperparameter Optimization Chul Kim Inwhee Joe 21 2 0 10 Apr 2025
Gradient-based Sample Selection for Faster Bayesian Optimization Qiyu Wei Haowei Wang Zirui Cao Songhao Wang Richard Allmendinger Mauricio A Álvarez 19 0 0 10 Apr 2025
Why risk matters for protein binder design Tudor-Stefan Cotet Igor Krawczuk 41 0 0 31 Mar 2025
Sample-Efficient Bayesian Transfer Learning for Online Machine Parameter Optimization Philipp Wagner Tobias Nagel Philipp Leube Marco F. Huber 58 0 0 20 Mar 2025
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization Toby Boyne Jose Pablo Folch Robert M. Lee B. Shafei Ruth Misener GP 59 0 0 07 Mar 2025
Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do? Anastasia S. Georgiou Daniel Jungen Luise F. Kaven Verena Hunstig Constantine Frangakis Ioannis G. Kevrekidis Alexander Mitsos 41 0 0 05 Mar 2025
Active Alignments of Lens Systems with Reinforcement Learning Matthias Burkhardt Tobias Schmähling Michael Layh Tobias Windisch 29 0 0 03 Mar 2025
Causal Discovery via Bayesian Optimization Bao Duong Sunil Gupta Thin Nguyen 39 0 0 28 Jan 2025
Tiered Acquisition for Constrained Bayesian Optimization: An Application to Analog Circuits Ria Rashid Abhishek Gupta 31 0 0 23 Dec 2024
EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization Mujin Cheon Jay H. Lee Dong-Yeun Koh Calvin Tsay 26 0 0 31 Oct 2024
Measurements with Noise: Bayesian Optimization for Co-optimizing Noise and Property Discovery in Automated Experiments Boris N. Slautin Yu Liu Jan Dec Vladimir V. Shvartsman Doru C. Lupascu M. Ziatdinov Sergei V. Kalinin 24 0 0 03 Oct 2024
Surrogate-Assisted Search with Competitive Knowledge Transfer for Expensive Optimization Xiaoming Xue Yao Hu Liang Feng Kai Zhang Linqi Song Kay Chen Tan 23 3 0 13 Aug 2024
A UAV-assisted Wireless Localization Challenge on AERPAW Paul S. Kudyba Jaya Sravani Mandapaka Weijie Wang Logan McCorkendale Zachary McCorkendale ... Eric Adams K. Namuduri Fraida Fund Mihail L. Sichitiu Ozgur Ozdemir 26 2 0 16 Jul 2024
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences Miguel González Duque Richard Michael Simon Bartels Yevgen Zainchkovskyy Søren Hauberg Wouter Boomsma 32 4 0 07 Jun 2024
Bayesian Optimization of Functions over Node Subsets in Graphs Huidong Liang Xingchen Wan Xiaowen Dong 40 1 0 24 May 2024
On Constructing Algorithm Portfolios in Algorithm Selection for Computationally Expensive Black-box Optimization in the Fixed-budget Setting Takushi Yoshikawa Ryoji Tanabe 16 0 0 13 May 2024
Optimal Initialization of Batch Bayesian Optimization Jiuge Ren David Sweet 40 1 0 27 Apr 2024
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization Dawei Zhan 44 5 0 18 Apr 2024
A Tutorial on Gaussian Process Learning-based Model Predictive Control Jie Wang Youmin Zhang GP 23 0 0 02 Apr 2024
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo Shijie Zhong Wanggang Shen Tommie A. Catanach Xun Huan 32 4 0 26 Mar 2024
Model Uncertainty in Evolutionary Optimization and Bayesian Optimization: A Comparative Analysis Hao Hao Xiaoqun Zhang Aimin Zhou 22 3 0 21 Mar 2024
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods A. Mumuni F. Mumuni 60 4 0 13 Mar 2024
Bayesian optimization as a flexible and efficient design framework for sustainable process systems J. Paulson Calvin Tsay TPM 32 12 0 29 Jan 2024
Simulation Based Bayesian Optimization Roi Naveiro Becky Tang 11 0 0 19 Jan 2024
Risk-Controlling Model Selection via Guided Bayesian Optimization Bracha Laufer-Goldshtein Adam Fisch Regina Barzilay Tommi Jaakkola TPM 6 4 0 04 Dec 2023
Regret Optimality of GP-UCB Wenjia Wang Xiaowei Zhang Lu Zou 19 0 0 03 Dec 2023
Gradient and Uncertainty Enhanced Sequential Sampling for Global Fit Sven Lämmle Can Bogoclu K. Cremanns D. Roos 14 5 0 29 Sep 2023
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 30 12 0 02 Jul 2023
A Secure Federated Data-Driven Evolutionary Multi-objective Optimization Algorithm Qiqi Liu Yuping Yan P. Ligeti Yaochu Jin FedML 25 14 0 15 Oct 2022
Towards Fairness-Aware Multi-Objective Optimization Guo-Ding Yu Lianbo Ma W. Du WenLi Du Yaochu Jin FaML 15 7 0 22 Jul 2022
Towards Futuristic Autonomous Experimentation--A Surprise-Reacting Sequential Experiment Policy Imtiaz Ahmed Satish Bukkapatnam Bhaskar Botcha Yucheng Ding 14 5 0 01 Dec 2021
A Federated Data-Driven Evolutionary Algorithm Jinjin Xu Yaochu Jin W. Du Sai Gu FedML 57 35 0 16 Feb 2021
Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai K. H. Low Patrick Jaillet FedML 79 109 0 20 Oct 2020
Bayesian optimization of variable-size design space problems J. Pelamatti Loïc Brevault M. Balesdent El-Ghazali Talbi Yannick Guerin 13 29 0 06 Mar 2020
Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization Lukas P. Frohlich Edgar D. Klenske Julia Vinogradska Christian Daniel M. Zeilinger 32 36 0 07 Feb 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization Benjamin Letham Roberto Calandra Akshara Rai E. Bakshy 71 109 0 31 Jan 2020
Max-value Entropy Search for Efficient Bayesian Optimization Zi Wang Stefanie Jegelka 110 403 0 06 Mar 2017
Time-Varying Gaussian Process Bandit Optimization Ilija Bogunovic Jonathan Scarlett V. Cevher 56 95 0 25 Jan 2016
Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic Loic Le Gratiet AI4CE 86 291 0 02 Oct 2012