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Sentiment analysis with genetically evolved Gaussian kernels
Sentiment analysis consists of evaluating opinions or statements based on text analysis. Among the methods used to estimate the degree to which a text expresses a certain sentiment are those based on Gaussian Processes. ...
An Experimental Study in Adaptive Kernel Selection for Bayesian Optimization
Bayesian Optimization has been widely used along with Gaussian Processes for solving expensive-to-evaluate black-box optimization problems. Overall, this approach has shown good results, and particularly for parameter ...
Evolving Gaussian Process Kernels for Translation Editing Effort Estimation
In many Natural Language Processing problems the combination of machine learning and optimization techniques is essential. One of these problems is estimating the effort required to improve, under direct human supervision, ...
Bayesian Optimization Approaches for Massively Multi-modal Problems
The optimization of massively multi-modal functions is a challenging task, particularly for problems where the search space can lead the op- timization process to local optima. While evolutionary algorithms have been ...
Data generation approaches for topic classification in multilingual spoken dialog systems
The conception of spoken-dialog systems (SDS) usually faces the problem of extending or adapting the system to multiple languages. This implies the creation of modules specically for the new languages, which is a time ...