Batched Large-scale Bayesian Optimization in High-dimensional Spaces

5 June 2017

Papers citing "Batched Large-scale Bayesian Optimization in High-dimensional Spaces"

43 / 43 papers shown

Title
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization Natalie Maus Kyurae Kim Yimeng Zeng Haydn Thomas Jones Fangping Wan Marcelo Der Torossian Torres Cesar de la Fuente-Nunez Jacob R. Gardner 80 0 0 31 Jan 2025
Causal Discovery via Bayesian Optimization Bao Duong Sunil Gupta Thin Nguyen 44 0 0 28 Jan 2025
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes Yunyue Wei Vincent Zhuang Saraswati Soedarmadji Yanan Sui 132 0 0 31 Dec 2024
Respecting the limit:Bayesian optimization with a bound on the optimal value Hanyang Wang Juergen Branke Matthias Poloczek 40 0 0 07 Nov 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models Xinxing Shi Thomas Baldwin-McDonald Mauricio A. Álvarez 76 0 0 01 Jul 2024
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences Miguel González Duque Richard Michael Simon Bartels Yevgen Zainchkovskyy Søren Hauberg Wouter Boomsma 44 4 0 07 Jun 2024
Single and Multi-Objective Optimization Benchmark Problems Focusing on Human-Powered Aircraft Design Nobuo Namura 20 1 0 14 Dec 2023
Deep Kernel and Image Quality Estimators for Optimizing Robotic Ultrasound Controller using Bayesian Optimization Deepak Raina S. Chandrashekhara Richard M. Voyles J. Wachs S. K. Saha 39 6 0 11 Oct 2023
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 19 36 0 22 Apr 2023
Active Learning and Bayesian Optimization: a Unified Perspective to Learn with a Goal Francesco Di Fiore Michela Nardelli L. Mainini 37 22 0 02 Mar 2023
Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization Jiayu Zhao Renyu Yang Shenghao Qiu Zheng Wang 11 4 0 16 Feb 2023
A Bayesian Optimization approach for calibrating large-scale activity-based transport models S. Agriesti Vladimir Kuzmanovski Jaakko Hollmén C. Roncoli Bat-hen Nahmias-Biran 29 5 0 07 Feb 2023
Local Bayesian optimization via maximizing probability of descent Quan Nguyen Kaiwen Wu Jacob R. Gardner Roman Garnett 17 23 0 21 Oct 2022
Pareto Set Learning for Expensive Multi-Objective Optimization Xi Lin Zhiyuan Yang Xiao-Yan Zhang Qingfu Zhang 36 54 0 16 Oct 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 24 3 0 04 Aug 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 38 199 0 07 Jun 2022
A model aggregation approach for high-dimensional large-scale optimization Haowei Wang Ercong Zhang Szu Hui Ng Giulia Pedrielli 22 1 0 16 May 2022
Self-focusing virtual screening with active design space pruning David E. Graff Matteo Aldeghi Joseph A. Morrone K. E. Jordan Edward O. Pyzer-Knapp Connor W. Coley 29 24 0 03 May 2022
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes Felix Jimenez Matthias Katzfuss 13 10 0 02 Mar 2022
Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus Haydn Thomas Jones Juston Moore Matt J. Kusner John Bradshaw Jacob R. Gardner BDL 51 69 0 28 Jan 2022
Efficient Exploration in Binary and Preferential Bayesian Optimization T. Fauvel M. Chalk 22 7 0 18 Oct 2021
A portfolio approach to massively parallel Bayesian optimization M. Binois Nicholson T. Collier J. Ozik 24 9 0 18 Oct 2021
Scaling Bayesian Optimization With Game Theory L. Mathesen G. Pedrielli R. L. Smith 19 1 0 07 Oct 2021
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces Sam Daulton David Eriksson Maximilian Balandat E. Bakshy 22 105 0 22 Sep 2021
Scaling Gaussian Processes with Derivative Information Using Variational Inference Misha Padidar Xinran Zhu Leo Huang Jacob R. Gardner D. Bindel BDL 14 18 0 08 Jul 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 79 17 0 23 Apr 2021
Fast Design Space Exploration of Nonlinear Systems: Part I S. Narain Emily Mak Dana Chee Brendan Englot K. Pochiraju N. Jha Karthik Narayan 25 5 0 05 Apr 2021
Uncertainty quantification and exploration-exploitation trade-off in humans Antonio Candelieri Andrea Ponti F. Archetti 21 4 0 05 Feb 2021
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models Jeroen van Hoof Joaquin Vanschoren BDL 19 9 0 06 Jan 2021
High-Dimensional Bayesian Optimization via Tree-Structured Additive Models E. Han Ishank Arora Jonathan Scarlett TPM AI4CE 25 17 0 24 Dec 2020
Accelerating high-throughput virtual screening through molecular pool-based active learning David E. Graff E. Shakhnovich Connor W. Coley 87 142 0 13 Dec 2020
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 18 57 0 08 Nov 2020
Matérn Gaussian Processes on Graphs Viacheslav Borovitskiy I. Azangulov Alexander Terenin P. Mostowsky M. Deisenroth N. Durrande 13 78 0 29 Oct 2020
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search Linnan Wang Rodrigo Fonseca Yuandong Tian 35 126 0 01 Jul 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 27 82 0 15 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 13 34 0 09 Jun 2020
ENTMOOT: A Framework for Optimization over Ensemble Tree Models Alexander Thebelt Jan Kronqvist Miten Mistry Robert M. Lee Nathan Sudermann-Merx Ruth Misener 29 54 0 10 Mar 2020
Scalable Constrained Bayesian Optimization David Eriksson Matthias Poloczek 33 95 0 20 Feb 2020
Randomly Projected Additive Gaussian Processes for Regression Ian A. Delbridge D. Bindel A. Wilson 19 27 0 30 Dec 2019
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 33 449 0 03 Oct 2019
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly Kirthevasan Kandasamy Karun Raju Vysyaraju W. Neiswanger Biswajit Paria Christopher R. Collins J. Schneider Barnabás Póczós Eric P. Xing 29 174 0 15 Mar 2019
Practical Transfer Learning for Bayesian Optimization Matthias Feurer Benjamin Letham Frank Hutter E. Bakshy 55 34 0 06 Feb 2018
Max-value Entropy Search for Efficient Bayesian Optimization Zi Wang Stefanie Jegelka 110 403 0 06 Mar 2017