
HyperVAE: A Minimum Description Length Variational HyperEncoding Network
We propose a framework called HyperVAE for encoding distributions of dis...
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Distributionally Robust Bayesian Quadrature Optimization
Bayesian quadrature optimization (BQO) maximizes the expectation of an e...
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Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning
Prior access to domain knowledge could significantly improve the perform...
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Bayesian Optimization for Categorical and CategorySpecific Continuous Inputs
Many realworld functions are defined over both categorical and category...
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Bayesian functional optimisation with shape prior
Real world experiments are expensive, and thus it is important to reach ...
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Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling
Scientific experiments are usually expensive due to complex experimental...
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Incorporating Expert Prior in Bayesian Optimisation via Space Warping
Bayesian optimisation is a wellknown sampleefficient method for the op...
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Covariance Function PreTraining with mKernels for Accelerated Bayesian Optimisation
The paper presents a novel approach to direct covariance function learni...
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High Dimensional Bayesian Optimization Using Dropout
Scaling Bayesian optimization to high dimensions is challenging task as ...
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Rapid Bayesian optimisation for synthesis of short polymer fiber materials
The discovery of processes for the synthesis of new materials involves m...
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Kernel PreTraining in Feature Space via mKernels
This paper presents a novel approach to kernel tuning. The method presen...
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Practical Batch Bayesian Optimization for Less Expensive Functions
Bayesian optimization (BO) and its batch extensions are successful for o...
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Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives
In this paper we develop a Bayesian optimization based hyperparameter tu...
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Stable Bayesian Optimisation via Direct Stability Quantification
In this paper we consider the problem of finding stable maxima of expens...
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Multiobjective Bayesian optimisation with preferences over objectives
We present a Bayesian multiobjective optimisation algorithm that allows...
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Sparse Spectrum Gaussian Process for Bayesian Optimisation
We propose a novel sparse spectrum approximation of Gaussian process (GP...
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Accelerating Experimental Design by Incorporating Experimenter Hunches
Experimental design is a process of obtaining a product with target prop...
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Costaware Multiobjective Bayesian optimisation
The notion of expense in Bayesian optimisation generally refers to the u...
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Bayesian Optimization with Unknown Search Space
Applying Bayesian optimization in problems wherein the search space is u...
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Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
Scaling Bayesian optimisation (BO) to highdimensional search spaces is ...
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Sunil Gupta
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