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Meta-Learning Priors for Safe Bayesian Optimization
v1v2v3 (latest)

Meta-Learning Priors for Safe Bayesian Optimization

3 October 2022
Jonas Rothfuss
Christopher Koenig
Alisa Rupenyan
Andreas Krause
ArXiv (abs)PDFHTML

Papers citing "Meta-Learning Priors for Safe Bayesian Optimization"

14 / 14 papers shown
Title
A Survey of Machine Learning for Estimating Workload: Considering Unknown Tasks
A Survey of Machine Learning for Estimating Workload: Considering Unknown Tasks
Josh Bhagat Smith
Julie A. Adams
101
0
0
20 Mar 2024
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search
Yunchuan Zhang
Sangwoo Park
Osvaldo Simeone
105
5
0
14 Mar 2024
Streaming Gaussian Dirichlet Random Fields for Spatial Predictions of
  High Dimensional Categorical Observations
Streaming Gaussian Dirichlet Random Fields for Spatial Predictions of High Dimensional Categorical Observations
J. E. S. Soucie
H. Sosik
Y. Girdhar
BDL
70
0
0
23 Feb 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer
Global Safe Sequential Learning via Efficient Knowledge Transfer
Cen-You Li
Olaf Duennbier
Marc Toussaint
Barbara Rakitsch
Christoph Zimmer
130
2
0
22 Feb 2024
Active Few-Shot Fine-Tuning
Active Few-Shot Fine-Tuning
Jonas Hübotter
Bhavya Sukhija
Lenart Treven
Yarden As
Andreas Krause
106
1
0
13 Feb 2024
Scalable Meta-Learning with Gaussian Processes
Scalable Meta-Learning with Gaussian Processes
Petru Tighineanu
Lukas Großberger
P. Baireuther
Kathrin Skubch
Stefan Falkner
Julia Vinogradska
Felix Berkenkamp
77
5
0
01 Dec 2023
Data-Efficient Task Generalization via Probabilistic Model-based Meta
  Reinforcement Learning
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning
Arjun Bhardwaj
Jonas Rothfuss
Bhavya Sukhija
Yarden As
Marco Hutter
Stelian Coros
Andreas Krause
96
5
0
13 Nov 2023
Bayesian Optimization with Formal Safety Guarantees via Online Conformal
  Prediction
Bayesian Optimization with Formal Safety Guarantees via Online Conformal Prediction
Yunchuan Zhang
Sangwoo Park
Osvaldo Simeone
62
10
0
30 Jun 2023
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization
Daniel Widmer
Dong-oh Kang
Bhavya Sukhija
Jonas Hübotter
Andreas Krause
Stelian Coros
103
15
0
12 Jun 2023
META-SMGO-$Δ$: similarity as a prior in black-box optimization
META-SMGO-ΔΔΔ: similarity as a prior in black-box optimization
Riccardo Busetto
Valentina Breschi
Simone Formentin
88
0
0
30 Apr 2023
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 Practice
Jonas Rothfuss
Martin Josifoski
Vincent Fortuin
Andreas Krause
126
10
0
14 Nov 2022
Lifelong Bandit Optimization: No Prior and No Regret
Lifelong Bandit Optimization: No Prior and No Regret
Felix Schur
Parnian Kassraie
Jonas Rothfuss
Andreas Krause
101
3
0
27 Oct 2022
MARS: Meta-Learning as Score Matching in the Function Space
MARS: Meta-Learning as Score Matching in the Function Space
Krunoslav Lehman Pavasovic
Jonas Rothfuss
Andreas Krause
BDL
111
5
0
24 Oct 2022
GoSafeOpt: Scalable Safe Exploration for Global Optimization of
  Dynamical Systems
GoSafeOpt: Scalable Safe Exploration for Global Optimization of Dynamical Systems
Bhavya Sukhija
M. Turchetta
David Lindner
Andreas Krause
Sebastian Trimpe
Dominik Baumann
133
19
0
24 Jan 2022
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