Browsing by Author "Santana, R."
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Analysis of Dominant Classes in Universal Adversarial Perturbations
Vadillo, J.; Santana, R.; Lozano, J.A. (2022)The reasons why Deep Neural Networks are susceptible to being fooled by adversarial examples remains an open discussion. Indeed, many differ ent strategies can be employed to efficiently generate adversarial attacks, some ... 
Analysis of the sensitivity of the EndOfTurn Detection task to errors generated by the Automatic Speech Recognition process.
Montenegro, C.; Santana, R.; Lozano, J.A. (2021)An EndOfTurn Detection Module (EOTDM) is an essential component of au tomatic Spoken Dialogue Systems. The capability of correctly detecting whether a user’s utterance has ended or not improves the accuracy in interpreting ... 
Bayesian Optimization Approaches for Massively Multimodal Problems
Roman, I.; Mendiburu, A.; Santana, R.; Lozano, J.A. (2019)The optimization of massively multimodal 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
Montenegro, C.; Santana, R.; Lozano, J.A. (2019)The conception of spokendialog 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 ... 
Detection of Sand Dunes on Mars Using a Regular Vinebased Classification Approach
Carrera, D.; Bandeira, L.; Santana, R.; Lozano, J.A. (201808)This paper deals with the problem of detecting sand dunes from remotely sensed images of the surface of Mars. We build on previous approaches that propose methods to extract informative features for the classification of ... 
Evolving Gaussian Process Kernels for Translation Editing Effort Estimation
Roman, I.; Santana, R.; Mendiburu, A.; Lozano, J.A. (2019)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, ... 
An Experimental Study in Adaptive Kernel Selection for Bayesian Optimization
Roman, I.; Santana, R.; Mendiburu, A.; Lozano, J.A. (2019)Bayesian Optimization has been widely used along with Gaussian Processes for solving expensivetoevaluate blackbox optimization problems. Overall, this approach has shown good results, and particularly for parameter ... 
Exploring Gaps in DeepFool inSearch of More Effective Adversarial Perturbations
Vadillo, J.; Santana, R.; Lozano, J.A. (2021)Adversarial examples are inputs subtly perturbed to produce a wrong prediction in machine learning models, while remaining perceptually similar to the original input. To find adversarial examples, some attack strategies ... 
indepth analysis of SVM kernel learning and its components
Roman, I.; Santana, R.; Mendiburu, A.; Lozano, J.A. (2020)The performance of support vector machines in nonlinearlyseparable classification problems strongly relies on the kernel function. Towards an automatic machine learning approach for this technique, many research outputs ... 
An investigation of clustering strategies in manyobjective optimization: the IMulti algorithm as a case study
Castro, O.R.; Pozo, A.; Lozano, J.A.; Santana, R. (20170330)A variety of general strategies have been applied to enhance the performance of multiobjective optimization algorithms for manyobjective optimization problems (those with more than three objectives). One of these strategies ... 
perm mateda: A matlab toolbox of estimation of distribution algorithms for permutationbased combinatorial optimization problems
Irurozki, E.; Ceberio, J.; Santamaria, J.; Santana, R.; Mendiburu, A. (2018)Permutation problems are combinatorial optimization problems whose solutions are naturally codified as permutations. Due to their complexity, motivated principally by the factorial cardinality of the search space of ... 
Sentiment analysis with genetically evolved Gaussian kernels
Roman, I.; Santana, R.; Mendiburu, A.; Lozano, J.A. (2019)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. ...