$π$ BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization

23 April 2022

Papers citing "$π$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization"

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Title
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings Rong-Xi Tan Ming Chen Ke Xue Yao Wang Yaoyuan Wang Sheng Fu Chao Qian OffRL 39 0 0 08 Jun 2025
Hyperparameter Optimization via Interacting with Probabilistic Circuits Jonas Seng Fabrizio G. Ventola Zhongjie Yu Kristian Kersting TPM 74 0 0 23 May 2025
Auto-nnU-Net: Towards Automated Medical Image Segmentation Jannis Becktepe Leona Hennig Steffen Oeltze-Jafra Marius Lindauer 272 0 0 22 May 2025
FigBO: A Generalized Acquisition Function Framework with Look-Ahead Capability for Bayesian Optimization Hui Chen Xuhui Fan Zhangkai Wu Longbing Cao 94 0 0 28 Apr 2025
High Dimensional Bayesian Optimization using Lasso Variable Selection Vu Viet Hoang Hung The Tran Sunil R. Gupta Vu Nguyen 194 0 0 02 Apr 2025
Language-Based Bayesian Optimization Research Assistant (BORA) A. Cissé Xenophon Evangelopoulos V. Gusev Andrew I. Cooper 149 1 0 28 Jan 2025
Collaborative and Federated Black-box Optimization: A Bayesian Optimization Perspective Raed Al Kontar FedML 113 1 0 12 Nov 2024
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference Paul E. Chang Nasrulloh Loka Daolang Huang Ulpu Remes Samuel Kaski Luigi Acerbi AI4CE 124 8 0 20 Oct 2024
Principled Bayesian Optimisation in Collaboration with Human Experts Wenjie Xu Masaki Adachi Colin N. Jones Michael A. Osborne 90 3 0 14 Oct 2024
Optimizing Falsification for Learning-Based Control Systems: A Multi-Fidelity Bayesian Approach Zahra Shahrooei Mykel J. Kochenderfer Ali Baheri 73 1 0 12 Sep 2024
FastBO: Fast HPO and NAS with Adaptive Fidelity Identification Jiantong Jiang Ajmal Mian 119 0 0 01 Sep 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization Jacob O. Tørring Carl Hvarfner Luigi Nardi Magnus Sjalander 123 1 0 24 Jun 2024
Position: A Call to Action for a Human-Centered AutoML Paradigm Marius Lindauer Florian Karl A. Klier Julia Moosbauer Alexander Tornede Andreas Mueller Frank Hutter Matthias Feurer Bernd Bischl 94 8 0 05 Jun 2024
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior Shuyu Cheng Yibo Miao Yinpeng Dong Xiao Yang Xiao-Shan Gao Jun Zhu AAML 107 5 0 29 May 2024
Bayesian Optimization of Functions over Node Subsets in Graphs Huidong Liang Xingchen Wan Xiaowen Dong 123 1 0 24 May 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting Masaki Adachi Satoshi Hayakawa Martin Jørgensen Saad Hamid Harald Oberhauser Michael A. Osborne GP 97 3 0 18 Apr 2024
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties V. ArunKumarA. A. Shilton Sunil R. Gupta Santu Rana S. Greenhill Svetha Venkatesh 85 4 0 27 Feb 2024
auto-sktime: Automated Time Series Forecasting Marc-André Zöller Marius Lindauer Marco F. Huber AI4TS 113 0 0 13 Dec 2023
Expert-guided Bayesian Optimisation for Human-in-the-loop Experimental Design of Known Systems Tom Savage Ehecatl Antonio del Rio Chanona 106 2 0 05 Dec 2023
Domain Knowledge Injection in Bayesian Search for New Materials Zikai Xie Xenophon Evangelopoulos Joseph C. R. Thacker Andrew I. Cooper 59 3 0 26 Nov 2023
A General Framework for User-Guided Bayesian Optimization Carl Hvarfner Frank Hutter Luigi Nardi GP 102 14 0 24 Nov 2023
Looping in the Human Collaborative and Explainable Bayesian Optimization Masaki Adachi Brady Planden David A. Howey Michael A. Osborne Sebastian Orbell Natalia Ares Krikamol Maundet Siu Lun Chau 95 15 0 26 Oct 2023
BeBOP -- Combining Reactive Planning and Bayesian Optimization to Solve Robotic Manipulation Tasks Jonathan Styrud Matthias Mayr Erik Hellsten Volker Krueger Christian Smith 81 9 0 02 Oct 2023
Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning Joseph Giovanelli Alexander Tornede Tanja Tornede Marius Lindauer 99 7 0 07 Sep 2023
HypBO: Accelerating Black-Box Scientific Experiments Using Experts' Hypotheses A. Cissé Xenophon Evangelopoulos Sam Carruthers V. Gusev Andrew I. Cooper 69 4 0 22 Aug 2023
Learning Compliant Stiffness by Impedance Control-Aware Task Segmentation and Multi-objective Bayesian Optimization with Priors Masashi Okada Mayumi Komatsu Ryogo Okumura T. Taniguchi 74 5 0 28 Jul 2023
Robotic Sonographer: Autonomous Robotic Ultrasound using Domain Expertise in Bayesian Optimization Deepak Raina S. Chandrashekhara Richard M. Voyles J. Wachs S. K. Saha 74 16 0 05 Jul 2023
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning Neeratyoy Mallik Eddie Bergman Carl Hvarfner Daniel Stoll Maciej Janowski Marius Lindauer Luigi Nardi Frank Hutter 127 27 0 21 Jun 2023
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks Alexander Tornede Difan Deng Theresa Eimer Joseph Giovanelli Aditya Mohan ... Sarah Segel Daphne Theodorakopoulos Tanja Tornede Henning Wachsmuth Marius Lindauer 119 26 0 13 Jun 2023
Provably Efficient Bayesian Optimization with Unknown Gaussian Process Hyperparameter Estimation Huong Ha Vu-Linh Nguyen Hung Tran-The Hongyu Zhang Xiuzhen Zhang Anton Van Den Hengel 77 1 0 12 Jun 2023
Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach Masaki Adachi Satoshi Hayakawa Martin Jørgensen Xingchen Wan Vu Nguyen Harald Oberhauser Michael A. Osborne 119 6 0 09 Jun 2023
PFNs4BO: In-Context Learning for Bayesian Optimization Samuel G. Müller Matthias Feurer Noah Hollmann Frank Hutter 121 43 0 27 May 2023
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 81 42 0 22 Apr 2023
Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance Shuhei Watanabe 92 152 0 21 Apr 2023
Self-Correcting Bayesian Optimization through Bayesian Active Learning Carl Hvarfner E. Hellsten Frank Hutter Luigi Nardi GP 130 17 0 21 Apr 2023
BO-Muse: A human expert and AI teaming framework for accelerated experimental design Sunil R. Gupta A. Shilton V. ArunKumarA. S. Ryan Majid Abdolshah Hung Le Santu Rana Julian Berk Mahad Rashid Svetha Venkatesh 70 7 0 03 Mar 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning Adam X. Yang Laurence Aitchison Henry B. Moss 110 4 0 22 Feb 2023
SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces Masaki Adachi Satoshi Hayakawa Saad Hamid Martin Jørgensen Harald Oberhauser Michael A. Osborne 104 7 0 27 Jan 2023
Prior-mean-assisted Bayesian optimization application on FRIB Front-End tunning K. Hwang T. Maruta A. Plastun K. Fukushima Tong Zhang Qiang Zhao P. Ostroumov Yue Hao 20 5 0 11 Nov 2022
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources P. Mikkola Julien Martinelli Louis Filstroff Samuel Kaski 120 12 0 25 Oct 2022
Falsification of Cyber-Physical Systems using Bayesian Optimization Zahra Ramezani Kenan Sehic Luigi Nardi K. Åkesson 152 1 0 14 Sep 2022
Bayesian Optimization Augmented with Actively Elicited Expert Knowledge Daolang Huang Louis Filstroff P. Mikkola Runkai Zheng Samuel Kaski 64 5 0 18 Aug 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 87 3 0 04 Aug 2022
Learning Skill-based Industrial Robot Tasks with User Priors Matthias Mayr Carl Hvarfner Konstantinos Chatzilygeroudis Luigi Nardi Volker Krueger 82 21 0 02 Aug 2022
On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning Diane Wagner Fabio Ferreira Daniel Stoll R. Schirrmeister Samuel G. Müller Frank Hutter 87 18 0 16 Jul 2022
Improving Accuracy of Interpretability Measures in Hyperparameter Optimization via Bayesian Algorithm Execution Julia Moosbauer Giuseppe Casalicchio Marius Lindauer B. Bischl 65 2 0 11 Jun 2022
Joint Entropy Search for Maximally-Informed Bayesian Optimization Carl Hvarfner Frank Hutter Luigi Nardi 93 41 0 09 Jun 2022
Automated Dynamic Algorithm Configuration Steven Adriaensen André Biedenkapp Gresa Shala Noor H. Awad Theresa Eimer Marius Lindauer Frank Hutter 113 41 0 27 May 2022
Practitioner Motives to Use Different Hyperparameter Optimization Methods Niclas Kannengießer Niklas Hasebrook Felix Morsbach Marc-André Zöller Jörg Franke Marius Lindauer Frank Hutter Ali Sunyaev 84 0 0 03 Mar 2022
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 256 540 0 13 Jul 2021

πππBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization

Papers citing "$π$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization"

$π$ BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization