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The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

14 June 2016
Jian Wu
P. Frazier
    ODL
    BDL
ArXivPDFHTML

Papers citing "The Parallel Knowledge Gradient Method for Batch Bayesian Optimization"

48 / 48 papers shown
Title
Gradient-based Sample Selection for Faster Bayesian Optimization
Gradient-based Sample Selection for Faster Bayesian Optimization
Qiyu Wei
Haowei Wang
Zirui Cao
Songhao Wang
Richard Allmendinger
Mauricio A Álvarez
31
0
0
10 Apr 2025
Co-Learning Bayesian Optimization
Co-Learning Bayesian Optimization
Zhendong Guo
Yew-Soon Ong
Tiantian He
Haitao Liu
99
2
0
23 Jan 2025
Distributed Thompson sampling under constrained communication
Distributed Thompson sampling under constrained communication
Saba Zerefa
Zhaolin Ren
Haitong Ma
Na Li
41
1
0
03 Jan 2025
Pseudo-Bayesian Optimization
Pseudo-Bayesian Optimization
Haoxian Chen
Henry Lam
32
2
0
15 Oct 2023
On Active Learning for Gaussian Process-based Global Sensitivity
  Analysis
On Active Learning for Gaussian Process-based Global Sensitivity Analysis
Mohit Chauhan
Mariel A. Ojeda-Tuz
R. Catarelli
K. Gurley
Dimitrios Tsapetis
Michael D. Shields
18
12
0
27 Aug 2023
Memory-Based Dual Gaussian Processes for Sequential Learning
Memory-Based Dual Gaussian Processes for Sequential Learning
Paul E. Chang
Prakhar Verma
S. T. John
Arno Solin
Mohammad Emtiyaz Khan
GP
28
4
0
06 Jun 2023
Is novelty predictable?
Is novelty predictable?
Clara Fannjiang
Jennifer Listgarten
AI4CE
17
14
0
01 Jun 2023
Protein Sequence Design with Batch Bayesian Optimisation
Protein Sequence Design with Batch Bayesian Optimisation
Chuanjiao Zong
26
0
0
18 Mar 2023
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian Optimization
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian Optimization
Haitong Ma
Tianpeng Zhang
Yixuan Wu
Flavio du Pin Calmon
Na Li
26
10
0
10 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
16
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
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
33
6
0
02 Nov 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
39
54
0
16 Oct 2022
Multi-step Planning for Automated Hyperparameter Optimization with
  OptFormer
Multi-step Planning for Automated Hyperparameter Optimization with OptFormer
Lucio Dery
A. Friesen
Nando de Freitas
MarcÁurelio Ranzato
Yutian Chen
47
0
0
10 Oct 2022
PropertyDAG: Multi-objective Bayesian optimization of partially ordered,
  mixed-variable properties for biological sequence design
PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design
Ji Won Park
Samuel Stanton
Saeed Saremi
Andrew Watkins
Henri Dwyer
Vladimir Gligorijević
Richard Bonneau
Stephen Ra
Kyunghyun Cho
37
11
0
08 Oct 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies
Generalizing Bayesian Optimization with Decision-theoretic Entropies
Willie Neiswanger
Lantao Yu
Shengjia Zhao
Chenlin Meng
Stefano Ermon
UQCV
45
11
0
04 Oct 2022
On the Finite-Time Performance of the Knowledge Gradient Algorithm
On the Finite-Time Performance of the Knowledge Gradient Algorithm
Yanwen Li
Siyang Gao
19
4
0
14 Jun 2022
Recent Advances in Bayesian Optimization
Recent Advances in Bayesian Optimization
Xilu Wang
Yaochu Jin
Sebastian Schmitt
Markus Olhofer
40
200
0
07 Jun 2022
Fair and Green Hyperparameter Optimization via Multi-objective and
  Multiple Information Source Bayesian Optimization
Fair and Green Hyperparameter Optimization via Multi-objective and Multiple Information Source Bayesian Optimization
Antonio Candelieri
Andrea Ponti
Francesco Archetti
33
16
0
18 May 2022
Adjusted Expected Improvement for Cumulative Regret Minimization in
  Noisy Bayesian Optimization
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
Shouri Hu
Haowei Wang
Zhongxiang Dai
K. H. Low
Szu Hui Ng
33
4
0
10 May 2022
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian
  Processes
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes
Felix Jimenez
Matthias Katzfuss
21
10
0
02 Mar 2022
Fast online inference for nonlinear contextual bandit based on
  Generative Adversarial Network
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network
Yun-Da Tsai
Shou-De Lin
46
5
0
17 Feb 2022
Thinking inside the box: A tutorial on grey-box Bayesian optimization
Thinking inside the box: A tutorial on grey-box Bayesian optimization
Raul Astudillo
P. Frazier
28
35
0
02 Jan 2022
Bayesian Optimization of Function Networks
Bayesian Optimization of Function Networks
Raul Astudillo
P. Frazier
32
36
0
31 Dec 2021
A portfolio approach to massively parallel Bayesian optimization
A portfolio approach to massively parallel Bayesian optimization
M. Binois
Nicholson T. Collier
J. Ozik
27
9
0
18 Oct 2021
Lookahead Acquisition Functions for Finite-Horizon Time-Dependent
  Bayesian Optimization and Application to Quantum Optimal Control
Lookahead Acquisition Functions for Finite-Horizon Time-Dependent Bayesian Optimization and Application to Quantum Optimal Control
Sudharshan Ashwin Renganathan
Jeffrey Larson
Stefan M. Wild
23
7
0
20 May 2021
Bayesian Optimization is Superior to Random Search for Machine Learning
  Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Ryan Turner
David Eriksson
M. McCourt
J. Kiili
Eero Laaksonen
Zhen Xu
Isabelle M Guyon
BDL
30
289
0
20 Apr 2021
MetaTune: Meta-Learning Based Cost Model for Fast and Efficient
  Auto-tuning Frameworks
MetaTune: Meta-Learning Based Cost Model for Fast and Efficient Auto-tuning Frameworks
Jaehun Ryu
Hyojin Sung
57
16
0
08 Feb 2021
Asynchronous ε-Greedy Bayesian Optimisation
Asynchronous ε-Greedy Bayesian Optimisation
George De Ath
Richard Everson
J. Fieldsend
35
5
0
15 Oct 2020
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
Shali Jiang
Daniel R. Jiang
Maximilian Balandat
Brian Karrer
Jacob R. Gardner
Roman Garnett
16
44
0
29 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models
Scalable Thompson Sampling using Sparse Gaussian Process Models
Sattar Vakili
Henry B. Moss
A. Artemev
Vincent Dutordoir
Victor Picheny
13
34
0
09 Jun 2020
Differentiable Expected Hypervolume Improvement for Parallel
  Multi-Objective Bayesian Optimization
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
Sam Daulton
Maximilian Balandat
E. Bakshy
11
236
0
09 Jun 2020
Sherpa: Robust Hyperparameter Optimization for Machine Learning
Sherpa: Robust Hyperparameter Optimization for Machine Learning
L. Hertel
Julian Collado
Peter Sadowski
J. Ott
Pierre Baldi
86
103
0
08 May 2020
$ε$-shotgun: $ε$-greedy Batch Bayesian Optimisation
εεε-shotgun: εεε-greedy Batch Bayesian Optimisation
George De Ath
Richard Everson
J. Fieldsend
Alma A. M. Rahat
29
15
0
05 Feb 2020
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
Maximilian Balandat
Brian Karrer
Daniel R. Jiang
Sam Daulton
Benjamin Letham
A. Wilson
E. Bakshy
32
93
0
14 Oct 2019
Scalable Global Optimization via Local Bayesian Optimization
Scalable Global Optimization via Local Bayesian Optimization
Samyam Rajbhandari
Michael Pearce
Jacob R. Gardner
Ryan D. Turner
Matthias Poloczek
51
452
0
03 Oct 2019
BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design
BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design
Shali Jiang
Henry Chai
Javier I. González
Roman Garnett
OffRL
32
49
0
10 Sep 2019
A tree-based radial basis function method for noisy parallel surrogate
  optimization
A tree-based radial basis function method for noisy parallel surrogate optimization
Chenchao Shou
Matthew West
17
2
0
21 Aug 2019
Towards Assessing the Impact of Bayesian Optimization's Own
  Hyperparameters
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters
Marius Lindauer
Matthias Feurer
Katharina Eggensperger
André Biedenkapp
Frank Hutter
20
18
0
19 Aug 2019
pySOT and POAP: An event-driven asynchronous framework for surrogate
  optimization
pySOT and POAP: An event-driven asynchronous framework for surrogate optimization
David Eriksson
D. Bindel
C. Shoemaker
11
56
0
30 Jul 2019
Knowledge Gradient for Selection with Covariates: Consistency and
  Computation
Knowledge Gradient for Selection with Covariates: Consistency and Computation
Liang Ding
L. Hong
Haihui Shen
Xiaowei Zhang
BDL
13
27
0
12 Jun 2019
Sampling Acquisition Functions for Batch Bayesian Optimization
Sampling Acquisition Functions for Batch Bayesian Optimization
Alessandro De Palma
Celestine Mendler-Dünner
Thomas Parnell
Andreea Anghel
H. Pozidis
39
13
0
22 Mar 2019
Asynchronous Batch Bayesian Optimisation with Improved Local
  Penalisation
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
A. Alvi
Binxin Ru
Jan-Peter Calliess
Stephen J. Roberts
Michael A. Osborne
29
44
0
29 Jan 2019
A Tutorial on Bayesian Optimization
A Tutorial on Bayesian Optimization
P. Frazier
GP
15
1,744
0
08 Jul 2018
Maximizing acquisition functions for Bayesian optimization
Maximizing acquisition functions for Bayesian optimization
James T. Wilson
Frank Hutter
M. Deisenroth
46
240
0
25 May 2018
Parallel and Distributed Thompson Sampling for Large-scale Accelerated
  Exploration of Chemical Space
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
José Miguel Hernández-Lobato
James Requeima
Edward O. Pyzer-Knapp
Alán Aspuru-Guzik
33
178
0
06 Jun 2017
Hyperparameter Optimization: A Spectral Approach
Hyperparameter Optimization: A Spectral Approach
Elad Hazan
Adam R. Klivans
Yang Yuan
27
118
0
02 Jun 2017
Online Meta-learning by Parallel Algorithm Competition
Online Meta-learning by Parallel Algorithm Competition
Stefan Elfwing
E. Uchibe
Kenji Doya
31
22
0
24 Feb 2017
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