Bayesian Optimization in a Billion Dimensions via Random Embeddings

9 January 2013

Papers citing "Bayesian Optimization in a Billion Dimensions via Random Embeddings"

50 / 71 papers shown

Title
Learning Low-Dimensional Embeddings for Black-Box Optimization Riccardo Busetto Manas Mejari Marco Forgione Alberto Bemporad Dario Piga 14 0 0 02 May 2025
Gradient-based Sample Selection for Faster Bayesian Optimization Qiyu Wei Haowei Wang Zirui Cao Songhao Wang Richard Allmendinger Mauricio A Álvarez 31 0 0 10 Apr 2025
Pushing the Limits of the Reactive Affine Shaker Algorithm to Higher Dimensions R. Battiti M. Brunato 64 0 0 18 Feb 2025
High-Dimensional Bayesian Optimization Using Both Random and Supervised Embeddings R. Priem Y. Diouane N. Bartoli S. Dubreuil P. Saves 62 1 0 02 Feb 2025
Active learning for affinity prediction of antibodies Alexandra Gessner Sebastian W. Ober Owen Vickery Dino Oglic Talip Uçar AI4CE 26 4 0 11 Jun 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
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 9 37 0 10 Feb 2024
Vanilla Bayesian Optimization Performs Great in High Dimensions Carl Hvarfner E. Hellsten Luigi Nardi 32 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
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation Fengxue Zhang Jialin Song James Bowden Alexander Ladd Yisong Yue Thomas Desautels Yuxin Chen 30 6 0 25 Jul 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial V. Nemani Luca Biggio Xun Huan Zhen Hu Olga Fink Anh Tran Yan Wang Xiaoge Zhang Chao Hu AI4CE 33 75 0 07 May 2023
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling Y. Yin Yu Wang Gang Xu 32 4 0 04 May 2023
Network Cascade Vulnerability using Constrained Bayesian Optimization Albert Y. S. Lam M. Anitescu A. Subramanyam 22 0 0 27 Apr 2023
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 21 36 0 22 Apr 2023
Gradient-Free Textual Inversion Zhengcong Fei Mingyuan Fan Junshi Huang DiffM 33 31 0 12 Apr 2023
A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments Arpan Biswas Yongtao Liu Nicole Creange Yu-Chen Liu S. Jesse Jan-Chi Yang Sergei V. Kalinin M. Ziatdinov Rama K Vasudevan 18 5 0 05 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
Robust Bayesian Target Value Optimization J. G. Hoffer Sascha Ranftl Bernhard C. Geiger 20 9 0 11 Jan 2023
Falsification of Cyber-Physical Systems using Bayesian Optimization Zahra Ramezani Kenan Sehic Luigi Nardi K. Åkesson 37 1 0 14 Sep 2022
Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization Leo Feng Padideh Nouri Aneri Muni Yoshua Bengio Pierre-Luc Bacon 116 4 0 13 Sep 2022
Optimistic Optimization of Gaussian Process Samples Julia Grosse Cheng Zhang Philipp Hennig GP 16 0 0 02 Sep 2022
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
Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach Arpan Biswas Rama K Vasudevan M. Ziatdinov Sergei V. Kalinin BDL DRL 19 10 0 30 Jun 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 38 200 0 07 Jun 2022
Automated Dynamic Algorithm Configuration Steven Adriaensen André Biedenkapp Gresa Shala Noor H. Awad Theresa Eimer Marius Lindauer Frank Hutter 32 36 0 27 May 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
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis Kirill Antonov E. Raponi Hao Wang Carola Doerr 25 10 0 28 Apr 2022
Randomized Maximum Likelihood via High-Dimensional Bayesian Optimization Valentin Breaz Richard D. Wilkinson 19 0 0 17 Apr 2022
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders Samuel Stanton Wesley J. Maddox Nate Gruver Phillip M. Maffettone E. Delaney Peyton Greenside A. Wilson BDL 38 89 0 23 Mar 2022
Sparse Bayesian Optimization Sulin Liu Qing Feng David Eriksson Benjamin Letham E. Bakshy 30 7 0 03 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 55 69 0 28 Jan 2022
Black-Box Tuning for Language-Model-as-a-Service Tianxiang Sun Yunfan Shao Hong Qian Xuanjing Huang Xipeng Qiu VLM 50 256 0 10 Jan 2022
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso Kenan Sehic Alexandre Gramfort Joseph Salmon Luigi Nardi 22 35 0 04 Nov 2021
A comparison of mixed-variables Bayesian optimization approaches Jhouben Cuesta Ramirez Rodolphe Le Riche O. Roustant G. Perrin Cédric Durantin A. Glière 19 17 0 30 Oct 2021
A machine learning approach for fighting the curse of dimensionality in global optimization J. Schumann Alejandro M. Aragón 23 2 0 28 Oct 2021
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation Ross M. Clarke E. T. Oldewage José Miguel Hernández-Lobato 28 9 0 20 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
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
High-Dimensional Bayesian Optimization with Multi-Task Learning for RocksDB Sami Alabed Eiko Yoneki 18 17 0 30 Mar 2021
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models Jeroen van Hoof Joaquin Vanschoren BDL 27 9 0 06 Jan 2021
Generative Melody Composition with Human-in-the-Loop Bayesian Optimization Yijun Zhou Yuki Koyama Masataka Goto Takeo Igarashi 34 21 0 07 Oct 2020
A One-bit, Comparison-Based Gradient Estimator HanQin Cai Daniel McKenzie W. Yin Zhenliang Zhang 30 17 0 06 Oct 2020
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis E. Raponi Hao Wang M. Bujny S. Boria Carola Doerr 31 31 0 02 Jul 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
Sequential Gallery for Interactive Visual Design Optimization Yuki Koyama Issei Sato Masataka Goto 14 76 0 08 May 2020
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems Anthony Corso Robert J. Moss Mark Koren Ritchie Lee Mykel J. Kochenderfer 19 169 0 06 May 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