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Maximizing acquisition functions for Bayesian optimization

Maximizing acquisition functions for Bayesian optimization

25 May 2018
James T. Wilson
Frank Hutter
M. Deisenroth
ArXivPDFHTML

Papers citing "Maximizing acquisition functions for Bayesian optimization"

50 / 117 papers shown
Title
Why risk matters for protein binder design
Why risk matters for protein binder design
Tudor-Stefan Cotet
Igor Krawczuk
43
0
0
31 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
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
Natalie Maus
Kyurae Kim
Yimeng Zeng
Haydn Thomas Jones
Fangping Wan
Marcelo Der Torossian Torres
Cesar de la Fuente-Nunez
Jacob R. Gardner
80
0
0
31 Jan 2025
Unexpected Improvements to Expected Improvement for Bayesian Optimization
Unexpected Improvements to Expected Improvement for Bayesian Optimization
Sebastian Ament
Sam Daulton
David Eriksson
Maximilian Balandat
E. Bakshy
51
69
0
08 Jan 2025
Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling
Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling
Aman Sinha
Payam Nikdel
Supratik Paul
Shimon Whiteson
76
0
0
26 Nov 2024
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Taiwo A. Adebiyi
Bach Do
Ruda Zhang
114
2
0
29 Oct 2024
Global Optimization of Gaussian Process Acquisition Functions Using a
  Piecewise-Linear Kernel Approximation
Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation
Yilin Xie
Shiqiang Zhang
J. Paulson
Calvin Tsay
28
5
0
22 Oct 2024
Batched Energy-Entropy acquisition for Bayesian Optimization
Batched Energy-Entropy acquisition for Bayesian Optimization
Felix Teufel
Carsten Stahlhut
J. Ferkinghoff-Borg
33
0
0
11 Oct 2024
Gaussian Process Thompson Sampling via Rootfinding
Gaussian Process Thompson Sampling via Rootfinding
Taiwo A. Adebiyi
Bach Do
Ruda Zhang
GP
25
3
0
10 Oct 2024
Process-constrained batch Bayesian approaches for yield optimization in
  multi-reactor systems
Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems
Markus Grimm
Sébastien Paul
Pierre Chainais
32
0
0
05 Aug 2024
Uncertainty-Guided Optimization on Large Language Model Search Trees
Uncertainty-Guided Optimization on Large Language Model Search Trees
Julia Grosse
Ruotian Wu
Ahmad Rashid
Philipp Hennig
Pascal Poupart
Agustinus Kristiadi
37
1
0
04 Jul 2024
Approximation-Aware Bayesian Optimization
Approximation-Aware Bayesian Optimization
Natalie Maus
Kyurae Kim
Geoff Pleiss
David Eriksson
John P. Cunningham
Jacob R. Gardner
29
2
0
06 Jun 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization
  via Probabilistic Lifting
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
29
3
0
18 Apr 2024
Model Uncertainty in Evolutionary Optimization and Bayesian
  Optimization: A Comparative Analysis
Model Uncertainty in Evolutionary Optimization and Bayesian Optimization: A Comparative Analysis
Hao Hao
Xiaoqun Zhang
Aimin Zhou
24
3
0
21 Mar 2024
Reinforced In-Context Black-Box Optimization
Reinforced In-Context Black-Box Optimization
Lei Song
Chenxiao Gao
Ke Xue
Chenyang Wu
Dong Li
Jianye Hao
Zongzhang Zhang
Chao Qian
32
3
0
27 Feb 2024
Stopping Bayesian Optimization with Probabilistic Regret Bounds
Stopping Bayesian Optimization with Probabilistic Regret Bounds
James T. Wilson
31
4
0
26 Feb 2024
FlexHB: a More Efficient and Flexible Framework for Hyperparameter
  Optimization
FlexHB: a More Efficient and Flexible Framework for Hyperparameter Optimization
Yang Zhang
Haiyang Wu
Yuekui Yang
43
0
0
21 Feb 2024
An Augmented Surprise-guided Sequential Learning Framework for
  Predicting the Melt Pool Geometry
An Augmented Surprise-guided Sequential Learning Framework for Predicting the Melt Pool Geometry
Ahmed Shoyeb Raihan
H. Khosravi
T. Bhuiyan
Imtiaz Ahmed
AI4CE
17
7
0
10 Jan 2024
Integrated Path Tracking with DYC and MPC using LSTM Based Tire Force
  Estimator for Four-wheel Independent Steering and Driving Vehicle
Integrated Path Tracking with DYC and MPC using LSTM Based Tire Force Estimator for Four-wheel Independent Steering and Driving Vehicle
Sungjin Lim
Bilal Sadiq
Yongsik Jin
Sangho Lee
Gyeungho Choi
Kanghyun Nam
Yongseob Lim
19
0
0
13 Dec 2023
A General Framework for User-Guided Bayesian Optimization
A General Framework for User-Guided Bayesian Optimization
Carl Hvarfner
Frank Hutter
Luigi Nardi
GP
44
11
0
24 Nov 2023
Bayesian Optimization of Function Networks with Partial Evaluations
Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong
Jiayue Wan
Raul Astudillo
Sam Daulton
Maximilian Balandat
P. Frazier
26
2
0
03 Nov 2023
Adaptive importance sampling for heavy-tailed distributions via
  $α$-divergence minimization
Adaptive importance sampling for heavy-tailed distributions via ααα-divergence minimization
Thomas Guilmeau
Nicola Branchini
Émilie Chouzenoux
Victor Elvira
34
2
0
25 Oct 2023
An Introduction to the Calibration of Computer Models
An Introduction to the Calibration of Computer Models
Richard D. Wilkinson
Christopher W. Lanyon
32
0
0
13 Oct 2023
Smartpick: Workload Prediction for Serverless-enabled Scalable Data
  Analytics Systems
Smartpick: Workload Prediction for Serverless-enabled Scalable Data Analytics Systems
Anshuman Mohapatra
Kwangsung Oh
24
2
0
25 Jul 2023
Physics-based Reduced Order Modeling for Uncertainty Quantification of
  Guided Wave Propagation using Bayesian Optimization
Physics-based Reduced Order Modeling for Uncertainty Quantification of Guided Wave Propagation using Bayesian Optimization
G. Drakoulas
T. Gortsas
D. Polyzos
32
2
0
18 Jul 2023
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Jia-Yu Pan
Stefan Falkner
Felix Berkenkamp
Joaquin Vanschoren
34
1
0
07 Jul 2023
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango
Fabio Ferreira
Arlind Kadra
Frank Hutter
Frank Hutter Josif Grabocka
29
15
0
06 Jun 2023
Is novelty predictable?
Is novelty predictable?
Clara Fannjiang
Jennifer Listgarten
AI4CE
17
14
0
01 Jun 2023
BOtied: Multi-objective Bayesian optimization with tied multivariate
  ranks
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks
Ji Won Park
Natavsa Tagasovska
Michael R. Maser
Stephen Ra
Kyunghyun Cho
24
6
0
01 Jun 2023
DATED: Guidelines for Creating Synthetic Datasets for Engineering Design
  Applications
DATED: Guidelines for Creating Synthetic Datasets for Engineering Design Applications
Cyril Picard
Jürg Schiffmann
Faez Ahmed
32
8
0
15 May 2023
NUBO: A Transparent Python Package for Bayesian Optimization
NUBO: A Transparent Python Package for Bayesian Optimization
Mike Diessner
Kevin J. Wilson
Richard D. Whalley
46
2
0
11 May 2023
Adaptive Experimentation at Scale: A Computational Framework for
  Flexible Batches
Adaptive Experimentation at Scale: A Computational Framework for Flexible Batches
Ethan Che
Hongseok Namkoong
OffRL
31
1
0
21 Mar 2023
BO-Muse: A human expert and AI teaming framework for accelerated
  experimental design
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
34
7
0
03 Mar 2023
Unleashing the Potential of Acquisition Functions in High-Dimensional
  Bayesian Optimization
Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization
Jiayu Zhao
Renyu Yang
Shenghao Qiu
Zheng Wang
11
4
0
16 Feb 2023
Scalable Bayesian optimization with high-dimensional outputs using
  randomized prior networks
Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks
Mohamed Aziz Bhouri
M. Joly
Robert Yu
S. Sarkar
P. Perdikaris
BDL
UQCV
AI4CE
19
1
0
14 Feb 2023
Stationary Kernels and Gaussian Processes on Lie Groups and their
  Homogeneous Spaces II: non-compact symmetric spaces
Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces
I. Azangulov
A. Smolensky
Alexander Terenin
Viacheslav Borovitskiy
32
14
0
30 Jan 2023
Cell-Free Data Power Control Via Scalable Multi-Objective Bayesian
  Optimisation
Cell-Free Data Power Control Via Scalable Multi-Objective Bayesian Optimisation
Sergey S. Tambovskiy
Gábor Fodor
H. Tullberg
12
3
0
20 Dec 2022
A Data-Driven Evolutionary Transfer Optimization for Expensive Problems
  in Dynamic Environments
A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments
Ke Li
Renzhi Chen
Xin Yao
24
14
0
05 Nov 2022
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning
Paul E. Chang
Prakhar Verma
S. T. John
Victor Picheny
Henry B. Moss
Arno Solin
GP
25
6
0
02 Nov 2022
Atlas: Automate Online Service Configuration in Network Slicing
Atlas: Automate Online Service Configuration in Network Slicing
Qiang Liu
Nakjung Choi
Tao Han
15
7
0
30 Oct 2022
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic
  Reparameterization
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
Sam Daulton
Xingchen Wan
David Eriksson
Maximilian Balandat
Michael A. Osborne
E. Bakshy
27
36
0
18 Oct 2022
Pareto Set Learning for Expensive Multi-Objective Optimization
Pareto Set Learning for Expensive Multi-Objective Optimization
Xi Lin
Zhiyuan Yang
Xiao-Yan Zhang
Qingfu Zhang
36
54
0
16 Oct 2022
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials
Cas van der Oord
Matthias Sachs
D. P. Kovács
Christoph Ortner
Gábor Csányi
41
64
0
09 Oct 2022
Joint Entropy Search for Multi-objective Bayesian Optimization
Joint Entropy Search for Multi-objective Bayesian Optimization
Ben Tu
Axel Gandy
N. Kantas
B. Shafei
21
38
0
06 Oct 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies
Generalizing Bayesian Optimization with Decision-theoretic Entropies
W. Neiswanger
Lantao Yu
Shengjia Zhao
Chenlin Meng
Stefano Ermon
UQCV
45
11
0
04 Oct 2022
Batch Bayesian optimisation via density-ratio estimation with guarantees
Batch Bayesian optimisation via density-ratio estimation with guarantees
Rafael Oliveira
Louis C. Tiao
Fabio Ramos
42
7
0
22 Sep 2022
Batch Bayesian Optimization via Particle Gradient Flows
Batch Bayesian Optimization via Particle Gradient Flows
Enrico Crovini
S. Cotter
K. Zygalakis
Andrew B. Duncan
13
3
0
10 Sep 2022
Bayesian Optimization with Informative Covariance
Bayesian Optimization with Informative Covariance
Afonso Eduardo
Michael U. Gutmann
24
3
0
04 Aug 2022
Investigating Bayesian optimization for expensive-to-evaluate black box
  functions: Application in fluid dynamics
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics
Mike Diessner
Joseph O’Connor
A. Wynn
S. Laizet
Yu Guan
Kevin J. Wilson
Richard D. Whalley
33
18
0
19 Jul 2022
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