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Gaussian Process Optimization with Mutual Information

Gaussian Process Optimization with Mutual Information

19 November 2013
E. Contal
Vianney Perchet
Nicolas Vayatis
ArXivPDFHTML

Papers citing "Gaussian Process Optimization with Mutual Information"

27 / 27 papers shown
Title
Distributed Multi-robot Source Seeking in Unknown Environments with Unknown Number of Sources
Lingpeng Chen
Siva Kailas
Srujan Deolasee
Wenhao Luo
Katia P. Sycara
Woojun Kim
51
0
0
14 Mar 2025
Efficient Parameter Tuning for a Structure-Based Virtual Screening HPC
  Application
Efficient Parameter Tuning for a Structure-Based Virtual Screening HPC Application
Bruno Guindani
Davide Gadioli
Roberto Rocco
Danilo Ardagna
G. Palermo
30
0
0
18 Oct 2024
Batched Stochastic Bandit for Nondegenerate Functions
Batched Stochastic Bandit for Nondegenerate Functions
Yu Liu
Yunlu Shu
Tianyu Wang
52
0
0
09 May 2024
Information-Theoretic Safe Bayesian Optimization
Information-Theoretic Safe Bayesian Optimization
A. Bottero
Carlos E. Luis
Julia Vinogradska
Felix Berkenkamp
Jan Peters
37
1
0
23 Feb 2024
Constraint-Guided Online Data Selection for Scalable Data-Driven Safety
  Filters in Uncertain Robotic Systems
Constraint-Guided Online Data Selection for Scalable Data-Driven Safety Filters in Uncertain Robotic Systems
Jason J. Choi
F. Castañeda
Wonsuhk Jung
Bike Zhang
Claire J. Tomlin
Koushil Sreenath
37
3
0
23 Nov 2023
Collaborative and Distributed Bayesian Optimization via Consensus:
  Showcasing the Power of Collaboration for Optimal Design
Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design
Xubo Yue
Raed Al Kontar
A. Berahas
Yang Liu
Blake N. Johnson
25
3
0
25 Jun 2023
Information-Theoretic Safe Exploration with Gaussian Processes
Information-Theoretic Safe Exploration with Gaussian Processes
A. Bottero
Carlos E. Luis
Julia Vinogradska
Felix Berkenkamp
Jan Peters
31
13
0
09 Dec 2022
End-to-End Learning of Deep Kernel Acquisition Functions for Bayesian
  Optimization
End-to-End Learning of Deep Kernel Acquisition Functions for Bayesian Optimization
Tomoharu Iwata
BDL
11
4
0
01 Nov 2021
Pre-trained Gaussian processes for Bayesian optimization
Pre-trained Gaussian processes for Bayesian optimization
Zehao Wang
George E. Dahl
Kevin Swersky
Chansoo Lee
Zachary Nado
Justin Gilmer
Jasper Snoek
Zoubin Ghahramani
65
40
0
16 Sep 2021
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian
  Modeling
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling
Kai Wang
Bryan Wilder
S. Suen
B. Dilkina
Milind Tambe
127
0
0
07 Jul 2021
Using Distance Correlation for Efficient Bayesian Optimization
Using Distance Correlation for Efficient Bayesian Optimization
T. Kanazawa
44
3
0
17 Feb 2021
Simple and Scalable Parallelized Bayesian Optimization
Simple and Scalable Parallelized Bayesian Optimization
Masahiro Nomura
19
1
0
24 Jun 2020
Bayesian Quadrature Optimization for Probability Threshold Robustness
  Measure
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure
S. Iwazaki
Yu Inatsu
Ichiro Takeuchi
TPM
26
11
0
22 Jun 2020
Time-varying Gaussian Process Bandit Optimization with Non-constant
  Evaluation Time
Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time
Hideaki Imamura
Nontawat Charoenphakdee
Futoshi Futami
Issei Sato
Junya Honda
Masashi Sugiyama
25
3
0
10 Mar 2020
Learning Arbitrary Quantities of Interest from Expensive Black-Box
  Functions through Bayesian Sequential Optimal Design
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design
Piyush Pandita
Nimish Awalgaonkar
Ilias Bilionis
Jitesh H. Panchal
23
1
0
16 Dec 2019
A Simple Heuristic for Bayesian Optimization with A Low Budget
A Simple Heuristic for Bayesian Optimization with A Low Budget
Masahiro Nomura
Kenshi Abe
26
1
0
18 Nov 2019
Statistical Learning and Estimation of Piano Fingering
Statistical Learning and Estimation of Piano Fingering
Eita Nakamura
Yasuyuki Saito
Kazuyoshi Yoshii
9
38
0
23 Apr 2019
Towards Practical Lipschitz Bandits
Towards Practical Lipschitz Bandits
Tianyu Wang
Weicheng Ye
Dawei Geng
Cynthia Rudin
14
1
0
26 Jan 2019
Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes
Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes
Jialin Song
Y. Tokpanov
Yuxin Chen
Dagny Fleischman
Katherine T Fountaine
H. Atwater
Yisong Yue
17
8
0
15 Nov 2018
A General Framework for Multi-fidelity Bayesian Optimization with
  Gaussian Processes
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes
Jialin Song
Yuxin Chen
Yisong Yue
6
101
0
02 Nov 2018
Towards Bursting Filter Bubble via Contextual Risks and Uncertainties
Towards Bursting Filter Bubble via Contextual Risks and Uncertainties
Rikiya Takahashi
Shunan Zhang
11
1
0
30 Jun 2017
Efficient batch-sequential Bayesian optimization with moments of
  truncated Gaussian vectors
Efficient batch-sequential Bayesian optimization with moments of truncated Gaussian vectors
Sébastien Marmin
C. Chevalier
D. Ginsbourger
23
13
0
09 Sep 2016
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Lisha Li
Kevin G. Jamieson
Giulia DeSalvo
Afshin Rostamizadeh
Ameet Talwalkar
38
2,292
0
21 Mar 2016
Optimization for Gaussian Processes via Chaining
Optimization for Gaussian Processes via Chaining
E. Contal
C. Malherbe
Nicolas Vayatis
53
7
0
19 Oct 2015
Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for
  Bayesian Inverse Problems
Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for Bayesian Inverse Problems
Shiwei Lan
T. Bui-Thanh
M. Christie
Mark Girolami
39
56
0
22 Jul 2015
Sequential Design with Mutual Information for Computer Experiments
  (MICE): Emulation of a Tsunami Model
Sequential Design with Mutual Information for Computer Experiments (MICE): Emulation of a Tsunami Model
Joakim Beck
S. Guillas
25
95
0
01 Oct 2014
Learning to Optimize via Information-Directed Sampling
Learning to Optimize via Information-Directed Sampling
Daniel Russo
Benjamin Van Roy
29
276
0
21 Mar 2014
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