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Adaptive and Safe Bayesian Optimization in High Dimensions via
  One-Dimensional Subspaces
v1v2 (latest)

Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces

International Conference on Machine Learning (ICML), 2019
8 February 2019
Johannes Kirschner
Mojmír Mutný
N. Hiller
R. Ischebeck
Andreas Krause
ArXiv (abs)PDFHTML

Papers citing "Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces"

50 / 85 papers shown
We Still Don't Understand High-Dimensional Bayesian Optimization
We Still Don't Understand High-Dimensional Bayesian Optimization
Colin Doumont
Donney Fan
Natalie Maus
Jacob R. Gardner
Henry B. Moss
Geoff Pleiss
AI4CE
130
2
0
10 Apr 2026
Local Entropy Search over Descent Sequences for Bayesian Optimization
Local Entropy Search over Descent Sequences for Bayesian Optimization
David Stenger
Armin Lindicke
Alexander von Rohr
Sebastian Trimpe
112
0
0
24 Nov 2025
Constrained Best Arm Identification with Tests for Feasibility
Constrained Best Arm Identification with Tests for Feasibility
Ting Cai
Kirthevasan Kandasamy
161
0
0
12 Nov 2025
Thompson Sampling via Fine-Tuning of LLMs
Thompson Sampling via Fine-Tuning of LLMs
Nicolas Menet
Aleksandar Terzić
Michael Hersche
Andreas Krause
Abbas Rahimi
250
0
0
15 Oct 2025
PepCompass: Navigating peptide embedding spaces using Riemannian Geometry
PepCompass: Navigating peptide embedding spaces using Riemannian Geometry
Marcin Mo.zejko
Adam Bielecki
Jurand Prądzyński
Marcin Traskowski
Antoni Janowski
...
Marcelo Der Torossian Torres
Cesar de la Fuente-Nunez
Paulina Szymczak
Michał Kmicikiewicz
Ewa Szczurek
304
0
0
02 Oct 2025
Enhancing Trust-Region Bayesian Optimization via Newton Methods
Enhancing Trust-Region Bayesian Optimization via Newton Methods
Quanlin Chen
Yiyu Chen
Jing Huo
Tianyu Ding
Yang Gao
Y. Chen
150
1
0
25 Aug 2025
Multi-Metric Adaptive Experimental Design under Fixed Budget with Validation
Multi-Metric Adaptive Experimental Design under Fixed Budget with Validation
Qining Zhang
Tanner Fiez
Yi Liu
Wenyang Liu
220
1
0
03 Jun 2025
Safety and optimality in learning-based control at low computational cost
Safety and optimality in learning-based control at low computational costIEEE Transactions on Automatic Control (TAC), 2025
Dominik Baumann
Krzysztof Kowalczyk
Cristian R. Rojas
K. Tiels
Pawel Wachel
237
2
0
12 May 2025
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From Simulated Nonparametric Functions
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From Simulated Nonparametric Functions
Cen-You Li
Marc Toussaint
Barbara Rakitsch
Christoph Zimmer
OffRL
961
0
0
26 Jan 2025
Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems
Safe Bayesian Optimization for the Control of High-Dimensional Embodied SystemsConference on Robot Learning (CoRL), 2024
Yunyue Wei
Zeji Yi
Hongda Li
Saraswati Soedarmadji
Yanan Sui
419
5
0
31 Dec 2024
High-Dimensional Bayesian Optimization via Random Projection of Manifold
  Subspaces
High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces
Quoc-Anh Hoang Nguyen
The Hung Tran
411
3
0
21 Dec 2024
Robotic Control Optimization Through Kernel Selection in Safe Bayesian
  Optimization
Robotic Control Optimization Through Kernel Selection in Safe Bayesian OptimizationIEEE International Conference on Robotics and Biomimetics (ROBIO), 2024
Lihao Zheng
Hongxuan Wang
Xiaocong Li
Jun Ma
P. Vadakkepat
176
1
0
12 Nov 2024
Principled Bayesian Optimisation in Collaboration with Human Experts
Principled Bayesian Optimisation in Collaboration with Human Experts
Wenjie Xu
Masaki Adachi
Colin N. Jones
Michael A. Osborne
470
5
0
14 Oct 2024
ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
ActSafe: Active Exploration with Safety Constraints for Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2024
Yarden As
Bhavya Sukhija
Lenart Treven
Carmelo Sferrazza
Stelian Coros
Andreas Krause
437
17
0
12 Oct 2024
A survey and benchmark of high-dimensional Bayesian optimization of
  discrete sequences
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequencesNeural Information Processing Systems (NeurIPS), 2024
Miguel González Duque
Richard Michael
Simon Bartels
Yevgen Zainchkovskyy
Søren Hauberg
Wouter Boomsma
264
25
0
07 Jun 2024
Minimizing UCB: a Better Local Search Strategy in Local Bayesian
  Optimization
Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization
Zheyi Fan
Wenyu Wang
Szu Hui Ng
Q. Hu
236
8
0
24 May 2024
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian
  Optimization
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian OptimizationNeural Information Processing Systems (NeurIPS), 2024
Anthony Bardou
Patrick Thiran
Giovanni Ranieri
219
6
0
23 May 2024
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Dawei Zhan
316
16
0
18 Apr 2024
On Safety in Safe Bayesian Optimization
On Safety in Safe Bayesian Optimization
Christian Fiedler
Johanna Menn
Lukas Kreisköther
Sebastian Trimpe
364
18
0
19 Mar 2024
Bayesian Optimization that Limits Search Region to Lower Dimensions
  Utilizing Local GPR
Bayesian Optimization that Limits Search Region to Lower Dimensions Utilizing Local GPRInternational Conference on Machine Learning and Applications (ICMLA), 2023
Yasunori Taguchi
H. Gangi
142
2
0
13 Mar 2024
Information-Theoretic Safe Bayesian Optimization
Information-Theoretic Safe Bayesian Optimization
A. Bottero
Carlos E. Luis
Julia Vinogradska
Felix Berkenkamp
Jan Peters
307
1
0
23 Feb 2024
Boundary Exploration for Bayesian Optimization With Unknown Physical
  Constraints
Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints
Yunsheng Tian
Ane Zuniga
Xinwei Zhang
Johannes P. Dürholt
Payel Das
Jie Chen
Wojciech Matusik
Mina Konakovic-Lukovic
248
7
0
12 Feb 2024
Safe Guaranteed Exploration for Non-linear Systems
Safe Guaranteed Exploration for Non-linear Systems
Manish Prajapat
Johannes Köhler
M. Turchetta
Andreas Krause
Melanie Zeilinger
310
12
0
09 Feb 2024
Vanilla Bayesian Optimization Performs Great in High Dimensions
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner
E. Hellsten
Luigi Nardi
494
87
0
03 Feb 2024
Towards Safe Multi-Task Bayesian Optimization
Towards Safe Multi-Task Bayesian OptimizationConference on Learning for Dynamics & Control (L4DC), 2023
Jannis O. Lübsen
Christian Hespe
Annika Eichler
406
5
0
12 Dec 2023
Learning Regions of Interest for Bayesian Optimization with Adaptive
  Level-Set Estimation
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set EstimationInternational Conference on Machine Learning (ICML), 2023
Fengxue Zhang
Jialin Song
James Bowden
Alexander Ladd
Yisong Yue
Thomas Desautels
Yuxin Chen
247
8
0
25 Jul 2023
Constrained Causal Bayesian Optimization
Constrained Causal Bayesian OptimizationInternational Conference on Machine Learning (ICML), 2023
Virginia Aglietti
Alan Malek
Ira Ktena
Silvia Chiappa
CML
238
9
0
31 May 2023
Relaxing the Additivity Constraints in Decentralized No-Regret
  High-Dimensional Bayesian Optimization
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian OptimizationInternational Conference on Learning Representations (ICLR), 2023
Anthony Bardou
Patrick Thiran
Thomas Begin
438
10
0
31 May 2023
Bayesian Optimization over High-Dimensional Combinatorial Spaces via
  Dictionary-based Embeddings
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based EmbeddingsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Aryan Deshwal
Sebastian Ament
Maximilian Balandat
E. Bakshy
J. Doppa
David Eriksson
404
36
0
03 Mar 2023
Unleashing the Potential of Acquisition Functions in High-Dimensional
  Bayesian Optimization
Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization
Jiayu Zhao
Renyu Yang
Shenghao Qiu
Zheng Wang
284
6
0
16 Feb 2023
A Bayesian Optimization approach for calibrating large-scale
  activity-based transport models
A Bayesian Optimization approach for calibrating large-scale activity-based transport modelsIEEE Open Journal of Intelligent Transportation Systems (JOITS), 2023
S. Agriesti
Vladimir Kuzmanovski
Jaakko Hollmén
C. Roncoli
Bat-hen Nahmias-Biran
252
13
0
07 Feb 2023
Are Random Decompositions all we need in High Dimensional Bayesian
  Optimisation?
Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?International Conference on Machine Learning (ICML), 2023
Juliusz Ziomek
Haitham Bou-Ammar
217
37
0
30 Jan 2023
Information-Theoretic Safe Exploration with Gaussian Processes
Information-Theoretic Safe Exploration with Gaussian ProcessesNeural Information Processing Systems (NeurIPS), 2022
A. Bottero
Carlos E. Luis
Julia Vinogradska
Felix Berkenkamp
Jan Peters
330
17
0
09 Dec 2022
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior:
  From Theory to Practice
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to PracticeJournal of machine learning research (JMLR), 2022
Jonas Rothfuss
Martin Josifoski
Vincent Fortuin
Andreas Krause
495
11
0
14 Nov 2022
MARS: Meta-Learning as Score Matching in the Function Space
MARS: Meta-Learning as Score Matching in the Function SpaceInternational Conference on Learning Representations (ICLR), 2022
Krunoslav Lehman Pavasovic
Jonas Rothfuss
Andreas Krause
BDL
484
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24 Oct 2022
Optimization on Manifolds via Graph Gaussian Processes
Optimization on Manifolds via Graph Gaussian ProcessesSIAM Journal on Mathematics of Data Science (SIMODS), 2022
Hwanwoo Kim
D. Sanz-Alonso
Ruiyi Yang
470
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20 Oct 2022
Multipoint-BAX: A New Approach for Efficiently Tuning Particle
  Accelerator Emittance via Virtual Objectives
Multipoint-BAX: A New Approach for Efficiently Tuning Particle Accelerator Emittance via Virtual Objectives
Sara Ayoub Miskovich
Willie Neiswanger
W. Colocho
C. Emma
Jacqueline Garrahan
T. Maxwell
C. Mayes
Stefano Ermon
A. Edelen
Daniel Ratner
382
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POLAR: Preference Optimization and Learning Algorithms for Robotics
POLAR: Preference Optimization and Learning Algorithms for Robotics
Maegan Tucker
Kejun Li
Yisong Yue
Aaron D. Ames
347
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08 Aug 2022
Log Barriers for Safe Black-box Optimization with Application to Safe
  Reinforcement Learning
Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement LearningJournal of machine learning research (JMLR), 2022
Ilnura N. Usmanova
Yarden As
Maryam Kamgarpour
Andreas Krause
OffRL
317
17
0
21 Jul 2022
Active Exploration via Experiment Design in Markov Chains
Active Exploration via Experiment Design in Markov ChainsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Mojmír Mutný
Tadeusz Janik
Andreas Krause
308
26
0
29 Jun 2022
Scalable First-Order Bayesian Optimization via Structured Automatic
  Differentiation
Scalable First-Order Bayesian Optimization via Structured Automatic DifferentiationInternational Conference on Machine Learning (ICML), 2022
Sebastian Ament
Daniel Schwalbe-Koda
243
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16 Jun 2022
High-Dimensional Bayesian Optimization with Constraints: Application to
  Powder Weighing
High-Dimensional Bayesian Optimization with Constraints: Application to Powder Weighing
Shoki Miyagawa
Atsuyoshi Yano
N. Sawada
Isamu Ogawa
255
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0
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Cooperative Multi-Agent Trajectory Generation with Modular Bayesian
  Optimization
Cooperative Multi-Agent Trajectory Generation with Modular Bayesian Optimization
Gilhyun Ryou
E. Tal
S. Karaman
209
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01 Jun 2022
Graph Machine Learning for Design of High-Octane Fuels
Graph Machine Learning for Design of High-Octane FuelsAIChE Journal (AIChE J.), 2022
Jan G. Rittig
Martin Ritzert
Artur M. Schweidtmann
Stefanie Winkler
Jana M. Weber
P. Morsch
K. Heufer
Martin Grohe
Alexander Mitsos
Manuel Dahmen
409
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01 Jun 2022
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert
  Spaces
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert SpacesNeural Information Processing Systems (NeurIPS), 2022
Mojmír Mutný
Andreas Krause
355
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0
26 May 2022
Adjusted Expected Improvement for Cumulative Regret Minimization in
  Noisy Bayesian Optimization
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Shouri Hu
Haowei Wang
Zhongxiang Dai
K. H. Low
Szu Hui Ng
325
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0
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Tuning Particle Accelerators with Safety Constraints using Bayesian
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Tuning Particle Accelerators with Safety Constraints using Bayesian OptimizationPhysical Review Accelerators and Beams (PRAB), 2022
Johannes Kirschner
Mojmír Mutný
Andreas Krause
J. C. D. Portugal
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J. Snuverink
330
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26 Mar 2022
Policy-Based Bayesian Experimental Design for Non-Differentiable
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Ellen R. Novoseller
Jeffrey Ichnowski
Huang Huang
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248
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GoSafeOpt: Scalable Safe Exploration for Global Optimization of
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