
Many Objective Bayesian Optimization
Some real problems require the evaluation of expensive and noisy objecti...
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A Similarity Measure of Gaussian Process Predictive Distributions
Some scenarios require the computation of a predictive distribution of a...
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An Artificial Consciousness Model and its relations with Philosophy of Mind
This work seeks to study the beneficial properties that an autonomous ag...
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Fuzzy Stochastic Timed Petri Nets for Causal properties representation
Imagery is frequently used to model, represent and communicate knowledge...
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Comparing BERT against traditional machine learning text classification
The BERT model has arisen as a popular stateoftheart machine learning...
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Parallel Predictive Entropy Search for Multiobjective Bayesian Optimization with Constraints
Realworld problems often involve the optimization of several objectives...
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Towards Automatic Bayesian Optimization: A first step involving acquisition functions
Bayesian Optimization is the state of the art technique for the optimiza...
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Fake News Detection by means of Uncertainty Weighted Causal Graphs
Society is experimenting changes in information consumption, as new info...
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A Machine Consciousness architecture based on Deep Learning and Gaussian Processes
Recent developments in machine learning have pushed the tasks that machi...
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Uncertainty Weighted Causal Graphs
Causality has traditionally been a scientific way to generate knowledge ...
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Multiclass Gaussian Process Classification with Noisy Inputs
It is a common practice in the supervised machine learning community to ...
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Suggesting Cooking Recipes Through Simulation and Bayesian Optimization
Cooking typically involves a plethora of decisions about ingredients and...
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Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks
The PC algorithm is a popular method for learning the structure of Gauss...
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Dealing with Categorical and Integervalued Variables in Bayesian Optimization with Gaussian Processes
Bayesian Optimization (BO) methods are useful for optimizing functions t...
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Dealing with Integervalued Variables in Bayesian Optimization with Gaussian Processes
Bayesian optimization (BO) methods are useful for optimizing functions t...
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Predictive Entropy Search for Multiobjective Bayesian Optimization with Constraints
This work presents PESMOC, Predictive Entropy Search for Multiobjective...
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Eduardo C. GarridoMerchán
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