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Scalable Thompson Sampling using Sparse Gaussian Process Models

9 June 2020

Papers citing "Scalable Thompson Sampling using Sparse Gaussian Process Models"

46 / 46 papers shown

Title
GPflux: A Library for Deep Gaussian Processes Vincent Dutordoir Hugh Salimbeni Eric Hambro John Mcleod Felix Leibfried A. Artemev Mark van der Wilk J. Hensman M. Deisenroth S. T. John GP 65 23 0 12 Apr 2021
Revisiting Bayesian Optimization in the light of the COCO benchmark Rodolphe Le Riche Victor Picheny 62 27 0 30 Mar 2021
GIBBON: General-purpose Information-Based Bayesian OptimisatioN Henry B. Moss David S. Leslie Javier I. González Paul Rayson 66 44 0 05 Feb 2021
Gaussian Process Molecule Property Prediction with FlowMO Henry B. Moss Ryan-Rhys Griffiths 91 23 0 02 Oct 2020
BOSS: Bayesian Optimization over String Spaces Henry B. Moss Daniel Beck Javier I. González David S. Leslie Paul Rayson 56 68 0 02 Oct 2020
On Information Gain and Regret Bounds in Gaussian Process Bandits Sattar Vakili Kia Khezeli Victor Picheny GP 60 135 0 15 Sep 2020
Sparse Gaussian Processes with Spherical Harmonic Features Vincent Dutordoir N. Durrande J. Hensman 69 55 0 30 Jun 2020
Matérn Gaussian processes on Riemannian manifolds Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 85 123 0 17 Jun 2020
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming Gabriel Riutort-Mayol Paul-Christian Bürkner Michael R. Andersen Arno Solin Aki Vehtari 64 71 0 23 Apr 2020
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 68 95 0 02 Mar 2020
Efficiently Sampling Functions from Gaussian Process Posteriors James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 56 165 0 21 Feb 2020
Scalable Constrained Bayesian Optimization David Eriksson Matthias Poloczek 68 99 0 20 Feb 2020
Bandit optimisation of functions in the Matérn kernel RKHS David Janz David R. Burt Javier I. González 42 45 0 28 Jan 2020
Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints Sam Daulton Shaun Singh Vashist Avadhanula Drew Dimmery E. Bakshy 55 13 0 02 Nov 2019
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 86 465 0 03 Oct 2019
Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems A. Teckentrup 39 67 0 31 Aug 2019
Sparse Spectrum Gaussian Process for Bayesian Optimization Ang Yang Cheng Li Santu Rana Sunil R. Gupta Svetha Venkatesh 42 5 0 21 Jun 2019
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret Daniele Calandriello Luigi Carratino A. Lazaric Michal Valko Lorenzo Rosasco GP 43 0 0 13 Mar 2019
Rates of Convergence for Sparse Variational Gaussian Process Regression David R. Burt C. Rasmussen Mark van der Wilk 56 154 0 08 Mar 2019
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Motonobu Kanagawa Philipp Hennig Dino Sejdinovic Bharath K. Sriperumbudur GP BDL 141 343 0 06 Jul 2018
Bayesian Optimization of Combinatorial Structures Ricardo Baptista Matthias Poloczek 83 137 0 22 Jun 2018
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations Biswajit Paria Kirthevasan Kandasamy Barnabás Póczós 140 130 0 30 May 2018
Approximation beats concentration? An approximation view on inference with smooth radial kernels M. Belkin 95 69 0 10 Jan 2018
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 163 486 0 21 Dec 2017
Replication or exploration? Sequential design for stochastic simulation experiments M. Binois Jiangeng Huang R. Gramacy M. Ludkovski 66 115 0 09 Oct 2017
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 117 76 0 16 Sep 2017
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 76 185 0 06 Jun 2017
Batched Large-scale Bayesian Optimization in High-dimensional Spaces Zi Wang Clement Gehring Pushmeet Kohli Stefanie Jegelka UQCV 54 214 0 05 Jun 2017
On Kernelized Multi-armed Bandits Sayak Ray Chowdhury Aditya Gopalan 116 460 0 03 Apr 2017
Variational Fourier features for Gaussian processes J. Hensman N. Durrande Arno Solin VLM 68 200 0 21 Nov 2016
GPflow: A Gaussian process library using TensorFlow A. G. Matthews Mark van der Wilk T. Nickson Keisuke Fujii A. Boukouvalas Pablo León-Villagrá Zoubin Ghahramani J. Hensman GP 78 666 0 27 Oct 2016
Random Feature Expansions for Deep Gaussian Processes Kurt Cutajar Edwin V. Bonilla Pietro Michiardi Maurizio Filippone BDL 44 144 0 14 Oct 2016
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization Jian Wu P. Frazier ODL BDL 48 225 0 14 Jun 2016
Batch Bayesian Optimization via Local Penalization Javier I. González Zhenwen Dai Philipp Hennig Neil D. Lawrence 77 356 0 29 May 2015
Scalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek Oren Rippel Kevin Swersky Ryan Kiros N. Satish N. Sundaram Md. Mostofa Ali Patwary P. Prabhat Ryan P. Adams BDL UQCV 95 1,043 0 19 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions José Miguel Hernández-Lobato Matthew W. Hoffman Zoubin Ghahramani 107 647 0 10 Jun 2014
Hilbert Space Methods for Reduced-Rank Gaussian Process Regression Arno Solin Simo Särkkä 206 217 0 21 Jan 2014
Thompson Sampling for Complex Bandit Problems Aditya Gopalan Shie Mannor Yishay Mansour 144 202 0 03 Nov 2013
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 107 1,232 0 26 Sep 2013
Thompson Sampling for 1-Dimensional Exponential Family Bandits N. Korda E. Kaufmann Rémi Munos 74 155 0 12 Jul 2013
Learning to Optimize Via Posterior Sampling Daniel Russo Benjamin Van Roy 198 702 0 11 Jan 2013
Thompson Sampling for Contextual Bandits with Linear Payoffs Shipra Agrawal Navin Goyal 195 1,004 0 15 Sep 2012
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 359 7,942 0 13 Jun 2012
Thompson Sampling: An Asymptotically Optimal Finite Time Analysis E. Kaufmann N. Korda Rémi Munos 162 588 0 18 May 2012
Entropy Search for Information-Efficient Global Optimization Philipp Hennig Christian J. Schuler 118 673 0 06 Dec 2011