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Distributionally Robust Bayesian Optimization
v1v2v3 (latest)

Distributionally Robust Bayesian Optimization

International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
20 February 2020
Johannes Kirschner
Ilija Bogunovic
Stefanie Jegelka
Andreas Krause
ArXiv (abs)PDFHTML

Papers citing "Distributionally Robust Bayesian Optimization"

50 / 55 papers shown
Bayesian Ambiguity Contraction-based Adaptive Robust Markov Decision Processes for Adversarial Surveillance Missions
Bayesian Ambiguity Contraction-based Adaptive Robust Markov Decision Processes for Adversarial Surveillance Missions
Jimin Choi
Max Z. Li
AAML
239
0
0
01 Dec 2025
Distributionally Robust Optimization via Diffusion Ambiguity Modeling
Distributionally Robust Optimization via Diffusion Ambiguity Modeling
Jiaqi Wen
Jianyi Yang
146
2
0
26 Oct 2025
DRO-InstructZero: Distributionally Robust Prompt Optimization for Large Language Models
DRO-InstructZero: Distributionally Robust Prompt Optimization for Large Language Models
Yangyang Li
115
1
0
17 Oct 2025
BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertainty
BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertainty
Akshay Kudva
J. Paulson
144
2
0
04 Oct 2025
Thompson Sampling in Function Spaces via Neural Operators
Thompson Sampling in Function Spaces via Neural Operators
Rafael Oliveira
Xuesong Wang
Kian Ming A. Chai
Edwin Bonilla
293
0
0
27 Jun 2025
Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion
Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion
Zeyang Zheng
Arman Hosseini
Dong Chen
Omid Shoghli
Arsalan Heydarian
219
0
0
04 Apr 2025
Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context
Wasserstein Distributionally Robust Bayesian Optimization with Continuous ContextInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
F. Micheli
Efe C. Balta
Anastasios Tsiamis
John Lygeros
269
1
0
26 Mar 2025
Performance Comparisons of Reinforcement Learning Algorithms for Sequential Experimental Design
Performance Comparisons of Reinforcement Learning Algorithms for Sequential Experimental Design
Yasir Zubayr Barlas
Kizito Salako
277
2
0
07 Mar 2025
One Set to Rule Them All: How to Obtain General Chemical Conditions via Bayesian Optimization over Curried Functions
One Set to Rule Them All: How to Obtain General Chemical Conditions via Bayesian Optimization over Curried Functions
Stefan P. Schmid
Ella M. Rajaonson
C. Ser
Mohammad Haddadnia
Shi Xuan Leong
Alán Aspuru-Guzik
Agustinus Kristiadi
Kjell Jorner
Felix Strieth-Kalthoff
383
0
0
26 Feb 2025
Differentiability and Approximation of Probability Functions under
  Gaussian Mixture Models: A Bayesian Approach
Differentiability and Approximation of Probability Functions under Gaussian Mixture Models: A Bayesian Approach
Gonzalo Contador
Pedro Pérez-Aros
Emilio Vilches
182
0
0
05 Nov 2024
Active Learning for Level Set Estimation Using Randomized Straddle
  Algorithms
Active Learning for Level Set Estimation Using Randomized Straddle Algorithms
Yu Inatsu
Shion Takeno
Kentaro Kutsukake
Ichiro Takeuchi
235
5
0
06 Aug 2024
Robust Entropy Search for Safe Efficient Bayesian Optimization
Robust Entropy Search for Safe Efficient Bayesian Optimization
D. Weichert
Alexander Kister
Sebastian Houben
Patrick Link
G. Ernis
AAML
379
1
0
29 May 2024
Regret Minimization via Saddle Point Optimization
Regret Minimization via Saddle Point OptimizationNeural Information Processing Systems (NeurIPS), 2024
Johannes Kirschner
Seyed Alireza Bakhtiari
Kushagra Chandak
Volodymyr Tkachuk
Csaba Szepesvári
240
2
0
15 Mar 2024
Stochastic Bayesian Optimization with Unknown Continuous Context
  Distribution via Kernel Density Estimation
Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density EstimationAAAI Conference on Artificial Intelligence (AAAI), 2023
Xiaobin Huang
Lei Song
Ke Xue
Chao Qian
376
3
0
16 Dec 2023
Sample Efficient Preference Alignment in LLMs via Active Exploration
Sample Efficient Preference Alignment in LLMs via Active Exploration
Viraj Mehta
Vikramjeet Das
Ojash Neopane
Yijia Dai
Ilija Bogunovic
Ilija Bogunovic
Willie Neiswanger
Stefano Ermon
Jeff Schneider
Willie Neiswanger
OffRL
457
11
0
01 Dec 2023
Distributionally Robust Model-based Reinforcement Learning with Large
  State Spaces
Distributionally Robust Model-based Reinforcement Learning with Large State SpacesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Shyam Sundhar Ramesh
Pier Giuseppe Sessa
Yifan Hu
Andreas Krause
Ilija Bogunovic
OOD
263
23
0
05 Sep 2023
Robust Bayesian Satisficing
Robust Bayesian SatisficingNeural Information Processing Systems (NeurIPS), 2023
Artun Saday
Yacsar Cahit Yildirim
Cem Tekin
300
3
0
16 Aug 2023
Partial identification of kernel based two sample tests with mismeasured
  data
Partial identification of kernel based two sample tests with mismeasured data
Ron Nafshi
Maggie Makar
222
0
0
07 Aug 2023
Adversarial Causal Bayesian Optimization
Adversarial Causal Bayesian OptimizationInternational Conference on Learning Representations (ICLR), 2023
Scott Sussex
Pier Giuseppe Sessa
A. Makarova
Andreas Krause
239
5
0
31 Jul 2023
Designing Fiduciary Artificial Intelligence
Designing Fiduciary Artificial IntelligenceConference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2023
Sebastian Benthall
David Shekman
250
9
0
27 Jul 2023
Learning Relevant Contextual Variables Within Bayesian Optimization
Learning Relevant Contextual Variables Within Bayesian OptimizationConference on Uncertainty in Artificial Intelligence (UAI), 2023
Julien Martinelli
Ayush Bharti
A. Tiihonen
S. T. John
Louis Filstroff
Sabina J. Sloman
Patrick Rinke
Samuel Kaski
415
0
0
23 May 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
213
37
0
30 Jan 2023
Bounding Box-based Multi-objective Bayesian Optimization of Risk
  Measures under Input Uncertainty
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input UncertaintyInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Yu Inatsu
Shion Takeno
Hiroyuki Hanada
Kazuki Iwata
Ichiro Takeuchi
207
7
0
27 Jan 2023
Robust Bayesian Target Value Optimization
Robust Bayesian Target Value OptimizationComputers & industrial engineering (CIE), 2023
J. G. Hoffer
Sascha Ranftl
Bernhard C. Geiger
233
10
0
11 Jan 2023
Near-optimal Policy Identification in Active Reinforcement Learning
Near-optimal Policy Identification in Active Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2022
Xiang Li
Viraj Mehta
Johannes Kirschner
I. Char
Willie Neiswanger
J. Schneider
Andreas Krause
Ilija Bogunovic
OffRL
250
8
0
19 Dec 2022
Mind the Gap: Measuring Generalization Performance Across Multiple
  Objectives
Mind the Gap: Measuring Generalization Performance Across Multiple ObjectivesInternational Symposium on Intelligent Data Analysis (IDA), 2022
Matthias Feurer
Katharina Eggensperger
Eddie Bergman
Florian Pfisterer
J. Herbinger
Katharina Eggensperger
295
6
0
08 Dec 2022
Data-Driven Offline Decision-Making via Invariant Representation
  Learning
Data-Driven Offline Decision-Making via Invariant Representation LearningNeural Information Processing Systems (NeurIPS), 2022
Qi
Yi-Hsun Su
Aviral Kumar
Sergey Levine
OffRL
349
36
0
21 Nov 2022
Movement Penalized Bayesian Optimization with Application to Wind Energy
  Systems
Movement Penalized Bayesian Optimization with Application to Wind Energy SystemsNeural Information Processing Systems (NeurIPS), 2022
Shyam Sundhar Ramesh
Pier Giuseppe Sessa
Andreas Krause
Ilija Bogunovic
222
14
0
14 Oct 2022
Recent Advances in Bayesian Optimization
Recent Advances in Bayesian OptimizationACM Computing Surveys (ACM CSUR), 2022
Xilu Wang
Yaochu Jin
Sebastian Schmitt
Markus Olhofer
409
482
0
07 Jun 2022
Expert-Calibrated Learning for Online Optimization with Switching Costs
Expert-Calibrated Learning for Online Optimization with Switching CostsProceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2022
Pengfei Li
Jianyi Yang
Shaolei Ren
276
13
0
18 Apr 2022
Distributionally Robust Bayesian Optimization with $\varphi$-divergences
Distributionally Robust Bayesian Optimization with φ\varphiφ-divergencesNeural Information Processing Systems (NeurIPS), 2022
Hisham Husain
Vu-Linh Nguyen
Anton Van Den Hengel
547
21
0
04 Mar 2022
Robust Multi-Objective Bayesian Optimization Under Input Noise
Robust Multi-Objective Bayesian Optimization Under Input NoiseInternational Conference on Machine Learning (ICML), 2022
Sam Daulton
Sait Cakmak
Maximilian Balandat
Michael A. Osborne
Enlu Zhou
E. Bakshy
AAML
331
54
0
15 Feb 2022
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian
  Process Bandits
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process BanditsNeural Information Processing Systems (NeurIPS), 2022
Ilija Bogunovic
Zihan Li
Andreas Krause
Jonathan Scarlett
325
11
0
03 Feb 2022
Bayesian Optimization for Distributionally Robust Chance-constrained
  Problem
Bayesian Optimization for Distributionally Robust Chance-constrained ProblemInternational Conference on Machine Learning (ICML), 2022
Yu Inatsu
Shion Takeno
Masayuki Karasuyama
Ichiro Takeuchi
227
13
0
31 Jan 2022
Thinking inside the box: A tutorial on grey-box Bayesian optimization
Thinking inside the box: A tutorial on grey-box Bayesian optimizationOnline World Conference on Soft Computing in Industrial Applications (WSCIA), 2021
Raul Astudillo
P. Frazier
242
49
0
02 Jan 2022
Misspecified Gaussian Process Bandit Optimization
Misspecified Gaussian Process Bandit OptimizationNeural Information Processing Systems (NeurIPS), 2021
Ilija Bogunovic
Andreas Krause
266
57
0
09 Nov 2021
Risk-averse Heteroscedastic Bayesian Optimization
Risk-averse Heteroscedastic Bayesian Optimization
A. Makarova
Ilnura N. Usmanova
Ilija Bogunovic
Andreas Krause
249
42
0
05 Nov 2021
Unsupervised Learning of Debiased Representations with Pseudo-Attributes
Unsupervised Learning of Debiased Representations with Pseudo-AttributesComputer Vision and Pattern Recognition (CVPR), 2021
Seonguk Seo
Joon-Young Lee
Bohyung Han
FaML
365
61
0
06 Aug 2021
Neural Contextual Bandits without Regret
Neural Contextual Bandits without Regret
Parnian Kassraie
Andreas Krause
OffRL
355
48
0
07 Jul 2021
Generalization Bounds with Minimal Dependency on Hypothesis Class via
  Distributionally Robust Optimization
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust OptimizationNeural Information Processing Systems (NeurIPS), 2021
Yibo Zeng
Henry Lam
405
10
0
21 Jun 2021
Distributionally Robust Optimization with Markovian Data
Distributionally Robust Optimization with Markovian DataInternational Conference on Machine Learning (ICML), 2021
Mengmeng Li
Tobias Sutter
Daniel Kuhn
195
11
0
12 Jun 2021
Robust Generalization despite Distribution Shift via Minimum
  Discriminating Information
Robust Generalization despite Distribution Shift via Minimum Discriminating InformationNeural Information Processing Systems (NeurIPS), 2021
Tobias Sutter
Andreas Krause
Daniel Kuhn
OOD
189
13
0
08 Jun 2021
Bias-Robust Bayesian Optimization via Dueling Bandits
Bias-Robust Bayesian Optimization via Dueling BanditsInternational Conference on Machine Learning (ICML), 2021
Johannes Kirschner
Andreas Krause
323
12
0
25 May 2021
Value-at-Risk Optimization with Gaussian Processes
Value-at-Risk Optimization with Gaussian ProcessesInternational Conference on Machine Learning (ICML), 2021
Q. Nguyen
Zhongxiang Dai
K. H. Low
Patrick Jaillet
239
34
0
13 May 2021
Automatic Termination for Hyperparameter Optimization
Automatic Termination for Hyperparameter Optimization
Anastasia Makarova
Huibin Shen
Valerio Perrone
Aaron Klein
Jean Baptiste Faddoul
Andreas Krause
Matthias Seeger
Cédric Archambeau
403
29
0
16 Apr 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based
  Deep Reinforcement Learning
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement LearningInternational Conference on Machine Learning (ICML), 2021
Sebastian Curi
Ilija Bogunovic
Andreas Krause
252
18
0
18 Mar 2021
Robust Bandit Learning with Imperfect Context
Robust Bandit Learning with Imperfect ContextAAAI Conference on Artificial Intelligence (AAAI), 2021
Jianyi Yang
Shaolei Ren
243
8
0
09 Feb 2021
Active learning for distributionally robust level-set estimation
Active learning for distributionally robust level-set estimationInternational Conference on Machine Learning (ICML), 2021
Yu Inatsu
S. Iwazaki
Ichiro Takeuchi
272
16
0
08 Feb 2021
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation
Alexander I. Cowen-Rivers
Wenlong Lyu
Rasul Tutunov
Zhi Wang
Antoine Grosnit
...
A. Maraval
Hao Jianye
Jun Wang
Jan Peters
H. Ammar
568
118
0
07 Dec 2020
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
Mean-Variance Analysis in Bayesian Optimization under UncertaintyInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
S. Iwazaki
Yu Inatsu
Ichiro Takeuchi
200
33
0
17 Sep 2020
12
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