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Vanilla Bayesian Optimization Performs Great in High Dimensions

3 February 2024

Papers citing "Vanilla Bayesian Optimization Performs Great in High Dimensions"

25 / 25 papers shown

Title
Unexpected Improvements to Expected Improvement for Bayesian Optimization Sebastian Ament Sam Daulton David Eriksson Maximilian Balandat E. Bakshy 80 81 0 08 Jan 2025
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features Oliver R. A. Dunbar Nicholas H. Nelsen Maya Mutic 129 7 0 30 Jun 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization Jacob O. Tørring Carl Hvarfner Luigi Nardi Magnus Sjalander 85 1 0 24 Jun 2024
Are Random Decompositions all we need in High Dimensional Bayesian Optimisation? Juliusz Ziomek Haitham Bou-Ammar 84 24 0 30 Jan 2023
Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization Lei Song Ke Xue Xiaobin Huang Chaojun Qian 99 34 0 04 Oct 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 54 3 0 04 Aug 2022
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso Kenan Sehic Alexandre Gramfort Joseph Salmon Luigi Nardi 83 39 0 04 Nov 2021
Local policy search with Bayesian optimization Sarah Müller Alexander von Rohr Sebastian Trimpe BDL 52 40 0 22 Jun 2021
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search Linnan Wang Rodrigo Fonseca Yuandong Tian 72 128 0 01 Jul 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization Benjamin Letham Roberto Calandra Akshara Rai E. Bakshy 93 115 0 31 Jan 2020
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 86 473 0 03 Oct 2019
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces Johannes Kirschner Mojmír Mutný N. Hiller R. Ischebeck Andreas Krause 74 149 0 08 Feb 2019
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 157 1,057 0 18 Oct 2018
Bayesian Optimization of Combinatorial Structures Ricardo Baptista Matthias Poloczek 83 137 0 22 Jun 2018
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups Paul Rolland Jonathan Scarlett Ilija Bogunovic Volkan Cevher 68 115 0 20 Feb 2018
High Dimensional Bayesian Optimization Using Dropout Cheng Li Sunil R. Gupta Santu Rana Vu Nguyen Svetha Venkatesh A. Shilton 45 130 0 15 Feb 2018
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning Zi Wang Chengtao Li Stefanie Jegelka Pushmeet Kohli 66 124 0 06 Mar 2017
Fast methods for training Gaussian processes on large data sets C. Moore A. J. Chua C. Berry J. Gair GP 45 41 0 05 Apr 2016
Active Learning of Linear Embeddings for Gaussian Processes Roman Garnett Michael A. Osborne Philipp Hennig GP 100 92 0 24 Oct 2013
Bayesian Optimization in a Billion Dimensions via Random Embeddings Ziyun Wang Frank Hutter M. Zoghi David Matheson Nando de Freitas 170 445 0 09 Jan 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 359 7,954 0 13 Jun 2012
Additive Gaussian Processes David Duvenaud H. Nickisch C. Rasmussen GP 99 330 0 19 Dec 2011
Convergence rates of efficient global optimization algorithms Adam D. Bull 129 641 0 18 Jan 2011
Bounding Standard Gaussian Tail Probabilities L. Duembgen 100 55 0 09 Dec 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design Niranjan Srinivas Andreas Krause Sham Kakade Matthias Seeger 149 1,623 0 21 Dec 2009