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A Tutorial on Bayesian Optimization of Expensive Cost Functions, with
  Application to Active User Modeling and Hierarchical Reinforcement Learning

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

12 December 2010
E. Brochu
Vlad M. Cora
Nando de Freitas
    GP
ArXiv (abs)PDFHTML

Papers citing "A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning"

50 / 691 papers shown
Title
Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals
Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals
Yan Zuo
Amir Dezfouli
Iadine Chadès
David Alexander
B. W. Muir
46
1
0
10 Feb 2022
A unified surrogate-based scheme for black-box and preference-based
  optimization
A unified surrogate-based scheme for black-box and preference-based optimization
Davide Previtali
M. Mazzoleni
A. Ferramosca
F. Previdi
36
0
0
03 Feb 2022
Bayesian Optimization For Multi-Objective Mixed-Variable Problems
Bayesian Optimization For Multi-Objective Mixed-Variable Problems
Haris Moazam Sheikh
P. Marcus
77
12
0
30 Jan 2022
AntBO: Towards Real-World Automated Antibody Design with Combinatorial
  Bayesian Optimisation
AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation
M. A. Khan
Alexander I. Cowen-Rivers
Antoine Grosnit
Derrick-Goh-Xin Deik
Philippe A. Robert
...
Rasul Tutunov
Dany Bou-Ammar
Jun Wang
Amos Storkey
Haitham Bou-Ammar
218
23
0
29 Jan 2022
SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies
  Learned in Simulation
SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies Learned in Simulation
Rituraj Kaushik
Karol Arndt
Ville Kyrki
75
9
0
27 Jan 2022
Automated Heart and Lung Auscultation in Robotic Physical Examinations
Automated Heart and Lung Auscultation in Robotic Physical Examinations
Yifan Zhu
A. Smith
Kris K. Hauser
44
11
0
24 Jan 2022
Low Regret Binary Sampling Method for Efficient Global Optimization of
  Univariate Functions
Low Regret Binary Sampling Method for Efficient Global Optimization of Univariate Functions
Kaan Gokcesu
Hakan Gokcesu
48
11
0
18 Jan 2022
A Comparative study of Hyper-Parameter Optimization Tools
A Comparative study of Hyper-Parameter Optimization Tools
Shashank Shekhar
Adesh Bansode
Asif Salim
36
49
0
17 Jan 2022
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression
Giacomo Meanti
Luigi Carratino
Ernesto De Vito
Lorenzo Rosasco
61
13
0
17 Jan 2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Jack Parker-Holder
Raghunandan Rajan
Xingyou Song
André Biedenkapp
Yingjie Miao
...
Vu-Linh Nguyen
Roberto Calandra
Aleksandra Faust
Frank Hutter
Marius Lindauer
AI4CE
116
107
0
11 Jan 2022
Automatic Configuration for Optimal Communication Scheduling in DNN
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Automatic Configuration for Optimal Communication Scheduling in DNN Training
Yiqing Ma
Hao Wang
Yiming Zhang
Kai Chen
35
12
0
27 Dec 2021
An Online Data-Driven Emergency-Response Method for Autonomous Agents in
  Unforeseen Situations
An Online Data-Driven Emergency-Response Method for Autonomous Agents in Unforeseen Situations
Glenn Maguire
Nicholas A. Ketz
Praveen K. Pilly
Jean-Baptiste Mouret
47
1
0
17 Dec 2021
Online Calibrated and Conformal Prediction Improves Bayesian
  Optimization
Online Calibrated and Conformal Prediction Improves Bayesian Optimization
Shachi Deshpande
Charles Marx
Volodymyr Kuleshov
85
8
0
08 Dec 2021
Active Sensing for Search and Tracking: A Review
Active Sensing for Search and Tracking: A Review
Luca Varotto
Angelo Cenedese
Andrea Cavallaro
50
13
0
04 Dec 2021
Episodic Policy Gradient Training
Episodic Policy Gradient Training
Hung Le
Majid Abdolshah
Thommen George Karimpanal
Kien Do
D. Nguyen
Svetha Venkatesh
BDLOffRL
68
6
0
03 Dec 2021
Bayesian Optimization for auto-tuning GPU kernels
Bayesian Optimization for auto-tuning GPU kernels
Floris-Jan Willemsen
Rob van Nieuwpoort
Ben van Werkhoven
40
21
0
26 Nov 2021
Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks
Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks
N. Ozaki
Kanta Yanagida
Takuya Chikazawa
N. Pushparaj
Naoya Takeishi
R. Hyodo
32
7
0
23 Nov 2021
Branching Time Active Inference: the theory and its generality
Branching Time Active Inference: the theory and its generality
Théophile Champion
Lancelot Da Costa
Howard L. Bowman
Marek Grze's
AI4CE
69
18
0
22 Nov 2021
Quality and Computation Time in Optimization Problems
Quality and Computation Time in Optimization Problems
Zhicheng He
57
0
0
20 Nov 2021
Multi-Objective Constrained Optimization for Energy Applications via
  Tree Ensembles
Multi-Objective Constrained Optimization for Energy Applications via Tree Ensembles
Alexander Thebelt
Calvin Tsay
Robert M. Lee
Nathan Sudermann-Merx
David Walz
T. Tranter
Ruth Misener
AI4CE
58
30
0
04 Nov 2021
Likelihood-Free Inference in State-Space Models with Unknown Dynamics
Likelihood-Free Inference in State-Space Models with Unknown Dynamics
Alexander Aushev
Thong Tran
Henri Pesonen
Andrew Howes
Samuel Kaski
65
1
0
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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
52
4
0
01 Nov 2021
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement
  Learning
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
H. Chung
Jungtaek Kim
Boris Knyazev
Jinhwi Lee
Graham W. Taylor
Jaesik Park
Minsu Cho
SSLOffRL
53
20
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29 Oct 2021
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge
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Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
M. Hutchinson
Alexander Terenin
Viacheslav Borovitskiy
So Takao
Yee Whye Teh
M. Deisenroth
78
22
0
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Gaussian Process Sampling and Optimization with Approximate Upper and
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Gaussian Process Sampling and Optimization with Approximate Upper and Lower Bounds
Vu-Linh Nguyen
M. Deisenroth
Michael A. Osborne
GP
88
3
0
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Diversified Sampling for Batched Bayesian Optimization with
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Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes
Elvis Nava
Mojmír Mutný
Andreas Krause
65
15
0
22 Oct 2021
A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization
  Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box
  Design Problems
A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box Design Problems
Arpan Biswas
Claudio Fuentes
C. Hoyle
53
3
0
16 Oct 2021
Pre-trained Language Models in Biomedical Domain: A Systematic Survey
Pre-trained Language Models in Biomedical Domain: A Systematic Survey
Benyou Wang
Qianqian Xie
Jiahuan Pei
Zhihong Chen
Prayag Tiwari
Zhao Li
Jie Fu
LM&MAAI4CE
154
171
0
11 Oct 2021
Scaling Bayesian Optimization With Game Theory
Scaling Bayesian Optimization With Game Theory
L. Mathesen
G. Pedrielli
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93
1
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Study of Signal Temporal Logic Robustness Metrics for Robotic Tasks
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Study of Signal Temporal Logic Robustness Metrics for Robotic Tasks Optimization
Akshay Dhonthi
Philipp Schillinger
Leonel Rozo
Daniele Nardi
68
4
0
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Gaussian Processes to speed up MCMC with automatic
  exploratory-exploitation effect
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25
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Faster Improvement Rate Population Based Training
Faster Improvement Rate Population Based Training
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Max Jaderberg
67
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Bayesian Optimization with Clustering and Rollback for CNN Auto Pruning
Bayesian Optimization with Clustering and Rollback for CNN Auto Pruning
Hanwei Fan
Jiandong Mu
W. Zhang
77
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Computationally Efficient High-Dimensional Bayesian Optimization via
  Variable Selection
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Yi Shen
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Non-smooth Bayesian Optimization in Tuning Problems
Non-smooth Bayesian Optimization in Tuning Problems
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Identifying Untrustworthy Samples: Data Filtering for Open-domain
  Dialogues with Bayesian Optimization
Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
Lei Shen
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LinEasyBO: Scalable Bayesian Optimization Approach for Analog Circuit
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Cumulative Regret Analysis of the Piyavskii--Shubert Algorithm and Its
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Adaptive unsupervised learning with enhanced feature representation for
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Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization
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Recent advances in Bayesian optimization with applications to parameter
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Philipp‐Immanuel Schneider
32
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Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian
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351
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Shaan Desai
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0
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An Efficient Batch Constrained Bayesian Optimization Approach for Analog
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Fan Yang
Changhao Yan
Dian Zhou
Xuan Zeng
83
67
0
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Machine Learning based optimization for interval uncertainty propagation
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29
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Learning Space Partitions for Path Planning
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79
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Nonmyopic Multifidelity Active Search
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120
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Reinforced Few-Shot Acquisition Function Learning for Bayesian
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