
BOSS: Bayesian Optimization over String Spaces
This article develops a Bayesian optimization (BO) method which acts dir...
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Multitask Causal Learning with Gaussian Processes
This paper studies the problem of learning the correlation structure of ...
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Structure Mapping for Transferability of Causal Models
Human beings learn causal models and constantly use them to transfer kno...
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Learning Inconsistent Preferences with Kernel Methods
We propose a probabilistic kernel approach for preferential learning fro...
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Preferential Batch Bayesian Optimization
Most research in Bayesian optimization (BO) has focused on direct feedba...
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Bandit optimisation of functions in the Matérn kernel RKHS
We consider the problem of optimising functions in the Reproducing kerne...
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Efficient nonmyopic Bayesian optimization and quadrature
Finitehorizon sequential decision problems arise naturally in many mach...
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MetaSurrogate Benchmarking for Hyperparameter Optimization
Despite the recent progress in hyperparameter optimization (HPO), availa...
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Automatic Discovery of PrivacyUtility Pareto Fronts
Differential privacy is a mathematical framework for privacypreserving ...
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Active MultiInformation Source Bayesian Quadrature
Bayesian quadrature (BQ) is a sampleefficient probabilistic numerical m...
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Deep Gaussian Processes for Multifidelity Modeling
Multifidelity methods are prominently used when cheaplyobtained, but p...
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Preferential Bayesian Optimization
Bayesian optimization (BO) has emerged during the last few years as an e...
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Correcting boundary overexploration deficiencies in Bayesian optimization with virtual derivative sign observations
Bayesian optimization () is a global optimization strategy designed to f...
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Variational Autoencoded Deep Gaussian Processes
We develop a scalable deep nonparametric generative model by augmenting...
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GLASSES: Relieving The Myopia Of Bayesian Optimisation
We present GLASSES: Global optimisation with LookAhead through Stochast...
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Batch Bayesian Optimization via Local Penalization
The popularity of Bayesian optimization methods for efficient exploratio...
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Bayesian Optimization for Synthetic Gene Design
We address the problem of synthetic gene design using Bayesian optimizat...
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Reproducing kernel Hilbert space based estimation of systems of ordinary differential equations
Nonlinear systems of differential equations have attracted the interest...
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Javier Gonzalez
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