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Regret Bounds for Expected Improvement Algorithms in Gaussian Process
  Bandit Optimization

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization

15 March 2022
Hung The Tran
Sunil R. Gupta
Santu Rana
Svetha Venkatesh
ArXivPDFHTML

Papers citing "Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization"

20 / 20 papers shown
Title
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
Hung The Tran
Sunil R. Gupta
Santu Rana
Svetha Venkatesh
42
3
0
10 May 2021
Efficient Exploration of Reward Functions in Inverse Reinforcement
  Learning via Bayesian Optimization
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization
Sreejith Balakrishnan
Q. Nguyen
Bryan Kian Hsiang Low
Harold Soh
61
26
0
17 Nov 2020
On Information Gain and Regret Bounds in Gaussian Process Bandits
On Information Gain and Regret Bounds in Gaussian Process Bandits
Sattar Vakili
Kia Khezeli
Victor Picheny
GP
58
133
0
15 Sep 2020
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search
  Spaces
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
Hung The Tran
Sunil R. Gupta
Santu Rana
Huong Ha
Svetha Venkatesh
53
6
0
05 Sep 2020
Safe Reinforcement Learning in Constrained Markov Decision Processes
Safe Reinforcement Learning in Constrained Markov Decision Processes
Akifumi Wachi
Yanan Sui
58
149
0
15 Aug 2020
Knowing The What But Not The Where in Bayesian Optimization
Knowing The What But Not The Where in Bayesian Optimization
Vu Nguyen
Michael A. Osborne
54
38
0
07 May 2019
No-Regret Bayesian Optimization with Unknown Hyperparameters
No-Regret Bayesian Optimization with Unknown Hyperparameters
Felix Berkenkamp
Angela P. Schoellig
Andreas Krause
TPM
48
75
0
10 Jan 2019
Adversarially Robust Optimization with Gaussian Processes
Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic
Jonathan Scarlett
Stefanie Jegelka
Volkan Cevher
GP
AAML
40
126
0
25 Oct 2018
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization
Jonathan Scarlett
Ilija Bogunovic
Volkan Cevher
66
101
0
31 May 2017
Improving the Expected Improvement Algorithm
Improving the Expected Improvement Algorithm
Chao Qin
Diego Klabjan
Daniel Russo
74
137
0
29 May 2017
Safe Model-based Reinforcement Learning with Stability Guarantees
Safe Model-based Reinforcement Learning with Stability Guarantees
Felix Berkenkamp
M. Turchetta
Angela P. Schoellig
Andreas Krause
176
851
0
23 May 2017
On Kernelized Multi-armed Bandits
On Kernelized Multi-armed Bandits
Sayak Ray Chowdhury
Aditya Gopalan
111
460
0
03 Apr 2017
Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian
  Process Hyper-Parameters
Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters
Ziyun Wang
Nando de Freitas
78
89
0
30 Jun 2014
Predictive Entropy Search for Efficient Global Optimization of Black-box
  Functions
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions
José Miguel Hernández-Lobato
Matthew W. Hoffman
Zoubin Ghahramani
99
647
0
10 Jun 2014
Finite-Time Analysis of Kernelised Contextual Bandits
Finite-Time Analysis of Kernelised Contextual Bandits
Michal Valko
N. Korda
Rémi Munos
I. Flaounas
N. Cristianini
185
273
0
26 Sep 2013
Thompson Sampling for Contextual Bandits with Linear Payoffs
Thompson Sampling for Contextual Bandits with Linear Payoffs
Shipra Agrawal
Navin Goyal
195
998
0
15 Sep 2012
Exponential Regret Bounds for Gaussian Process Bandits with
  Deterministic Observations
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
Nando de Freitas
Alex Smola
M. Zoghi
84
112
0
27 Jun 2012
Practical Bayesian Optimization of Machine Learning Algorithms
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek
Hugo Larochelle
Ryan P. Adams
353
7,936
0
13 Jun 2012
Convergence rates of efficient global optimization algorithms
Convergence rates of efficient global optimization algorithms
Adam D. Bull
119
641
0
18 Jan 2011
Gaussian Process Optimization in the Bandit Setting: No Regret and
  Experimental Design
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas
Andreas Krause
Sham Kakade
Matthias Seeger
146
1,619
0
21 Dec 2009
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