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Why Non-myopic Bayesian Optimization is Promising and How Far Should We
  Look-ahead? A Study via Rollout

Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout

4 November 2019
Xubo Yue
Raed Al Kontar
ArXivPDFHTML

Papers citing "Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout"

14 / 14 papers shown
Title
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
Qian Xie
Raul Astudillo
P. Frazier
Ziv Scully
Alexander Terenin
89
2
0
17 Jan 2025
Optimal Observation-Intervention Trade-Off in Optimisation Problems with
  Causal Structure
Optimal Observation-Intervention Trade-Off in Optimisation Problems with Causal Structure
K. Hammar
Neil Dhir
CML
15
0
0
05 Sep 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
Adam X. Yang
Laurence Aitchison
Henry B. Moss
29
4
0
22 Feb 2023
Bayesian Optimization Over Iterative Learners with Structured Responses:
  A Budget-aware Planning Approach
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach
Syrine Belakaria
J. Doppa
Nicolò Fusi
Rishit Sheth
30
7
0
25 Jun 2022
Recent Advances in Bayesian Optimization
Recent Advances in Bayesian Optimization
Xilu Wang
Yaochu Jin
Sebastian Schmitt
Markus Olhofer
38
199
0
07 Jun 2022
Towards Futuristic Autonomous Experimentation--A Surprise-Reacting
  Sequential Experiment Policy
Towards Futuristic Autonomous Experimentation--A Surprise-Reacting Sequential Experiment Policy
Imtiaz Ahmed
Satish Bukkapatnam
Bhaskar Botcha
Yucheng Ding
30
5
0
01 Dec 2021
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent:
  Convergence Guarantees and Empirical Benefits
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits
Hao Chen
Lili Zheng
Raed Al Kontar
Garvesh Raskutti
20
3
0
19 Nov 2021
Adaptive Sampling using POMDPs with Domain-Specific Considerations
Adaptive Sampling using POMDPs with Domain-Specific Considerations
G. Salhotra
Chris Denniston
D. Caron
Gaurav Sukhatme
16
6
0
23 Sep 2021
HyperJump: Accelerating HyperBand via Risk Modelling
HyperJump: Accelerating HyperBand via Risk Modelling
Pedro Mendes
Maria Casimiro
Paolo Romano
David Garlan
22
7
0
05 Aug 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
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
Efficient Rollout Strategies for Bayesian Optimization
Efficient Rollout Strategies for Bayesian Optimization
E. Lee
David Eriksson
Bolong Cheng
M. McCourt
D. Bindel
8
23
0
24 Feb 2020
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
Variational Inference of Joint Models using Multivariate Gaussian
  Convolution Processes
Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes
Xubo Yue
Raed Al Kontar
32
16
0
09 Mar 2019
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