High Dimensional Bayesian Optimisation and Bandits via Additive Models

5 March 2015

Papers citing "High Dimensional Bayesian Optimisation and Bandits via Additive Models"

50 / 71 papers shown

Title
Learning Low-Dimensional Embeddings for Black-Box Optimization Riccardo Busetto Manas Mejari Marco Forgione Alberto Bemporad Dario Piga 19 0 0 02 May 2025
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 77 9 0 17 Feb 2025
Cliqueformer: Model-Based Optimization with Structured Transformers J. Kuba Pieter Abbeel Sergey Levine OffRL AI4CE 62 2 0 17 Oct 2024
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization Dawei Zhan 54 5 0 18 Apr 2024
Bayesian Optimization with Adaptive Kernels for Robot Control Ruben Martinez-Cantin 14 37 0 10 Feb 2024
Vanilla Bayesian Optimization Performs Great in High Dimensions Carl Hvarfner E. Hellsten Luigi Nardi 34 17 0 03 Feb 2024
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 45 6 0 11 Oct 2023
Representing Additive Gaussian Processes by Sparse Matrices Lu Zou Haoyuan Chen Liang Ding 28 0 0 29 Apr 2023
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 24 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 16 4 0 16 Feb 2023
Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks Mohamed Aziz Bhouri M. Joly Robert Yu S. Sarkar P. Perdikaris BDL UQCV AI4CE 19 1 0 14 Feb 2023
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning Volodymyr Tkachuk Seyed Alireza Bakhtiari Johannes Kirschner Matej Jusup Ilija Bogunovic Csaba Szepesvári 32 4 0 08 Feb 2023
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds Shion Takeno Yu Inatsu Masayuki Karasuyama 30 13 0 03 Feb 2023
Robust Bayesian Target Value Optimization J. G. Hoffer Sascha Ranftl Bernhard C. Geiger 25 9 0 11 Jan 2023
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 24 3 0 04 Aug 2022
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics Mike Diessner Joseph O’Connor A. Wynn S. Laizet Yu Guan Kevin J. Wilson Richard D. Whalley 36 18 0 19 Jul 2022
Graph Neural Network Bandits Parnian Kassraie Andreas Krause Ilija Bogunovic 26 11 0 13 Jul 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 40 200 0 07 Jun 2022
Cooperative Multi-Agent Trajectory Generation with Modular Bayesian Optimization Gilhyun Ryou E. Tal S. Karaman 26 4 0 01 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
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes Felix Jimenez Matthias Katzfuss 21 10 0 02 Mar 2022
Parallel MCMC Without Embarrassing Failures Daniel Augusto R. M. A. de Souza Diego Mesquita Samuel Kaski Luigi Acerbi 42 11 0 22 Feb 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 58 69 0 28 Jan 2022
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
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 85 448 0 13 Jul 2021
Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling Kai Wang Bryan Wilder S. Suen B. Dilkina Milind Tambe 121 0 0 07 Jul 2021
A hyperparameter-tuning approach to automated inverse planning Kelsey Maass Aleksandr Aravkin Minsun Kim 19 3 0 14 May 2021
Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung The Tran Sunil R. Gupta Santu Rana Svetha Venkatesh 11 3 0 10 May 2021
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression Christian Fiedler C. Scherer Sebastian Trimpe GP 26 65 0 06 May 2021
Continuous black-box optimization with quantum annealing and random subspace coding Syun Izawa Koki Kitai Shu Tanaka R. Tamura Koji Tsuda 11 3 0 30 Apr 2021
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models Jeroen van Hoof Joaquin Vanschoren BDL 38 9 0 06 Jan 2021
Good practices for Bayesian Optimization of high dimensional structured spaces E. Siivola Javier I. González Andrei Paleyes Aki Vehtari 30 37 0 31 Dec 2020
High-Dimensional Bayesian Optimization via Tree-Structured Additive Models E. Han Ishank Arora Jonathan Scarlett TPM AI4CE 33 17 0 24 Dec 2020
Online Learning Demands in Max-min Fairness Kirthevasan Kandasamy Gur-Eyal Sela Joseph E. Gonzalez Michael I. Jordan Ion Stoica FaML 11 15 0 15 Dec 2020
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search Linnan Wang Rodrigo Fonseca Yuandong Tian 40 126 0 01 Jul 2020
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization Xingchen Ma Matthew B. Blaschko 21 7 0 21 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
Corruption-Tolerant Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause Jonathan Scarlett 30 51 0 04 Mar 2020
Distributionally Robust Bayesian Optimization Johannes Kirschner Ilija Bogunovic Stefanie Jegelka Andreas Krause 30 77 0 20 Feb 2020
Bayesian Optimization for Policy Search in High-Dimensional Systems via Automatic Domain Selection Lukas P. Frohlich Edgar D. Klenske Christian Daniel Melanie Zeilinger 18 12 0 21 Jan 2020
Randomly Projected Additive Gaussian Processes for Regression Ian A. Delbridge D. Bindel A. Wilson 27 27 0 30 Dec 2019
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization Hung The Tran Sunil R. Gupta Santu Rana Svetha Venkatesh 22 14 0 27 Nov 2019
Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning Adarsh Dave Jared M. Mitchell Kirthevasan Kandasamy S. Burke Biswajit Paria Barnabás Póczós J. Whitacre V. Viswanathan 41 119 0 22 Oct 2019
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 32 93 0 14 Oct 2019
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 48 450 0 03 Oct 2019
High Dimensional Bayesian Optimization via Supervised Dimension Reduction Miao Zhang Huiqi Li Steven W. Su 19 44 0 21 Jul 2019
Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization Jwala Dhamala S. Ghimire J. Sapp B. Horácek Linwei Wang MedIm 39 12 0 01 Jul 2019
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly Kirthevasan Kandasamy Karun Raju Vysyaraju Willie Neiswanger Biswajit Paria Christopher R. Collins J. Schneider Barnabás Póczós Eric Xing 29 174 0 15 Mar 2019