116 citations · 340 across the 21 of their papers we have counts for
25 papers
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification
Roberto Santana, Ivan Hidalgo-Cenalmor, Unai Garciarena +2
In some machine learning applications the availability of labeled instances for supervised classification is limited while unlabeled instances are abundant. Semi-supervised learnin…
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations
Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano +1
Several recent works encourage the use of a Bayesian framework when assessing performance and fairness metrics of a classification algorithm in a supervised setting. We propose the…
A Survey on Preserving Fairness Guarantees in Changing Environments
Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano +1
Human lives are increasingly being affected by the outcomes of automated decision-making systems and it is essential for the latter to be, not only accurate, but also fair. The lit…
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees
Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano
The statistical characteristics of instance-label pairs often change with time in practical scenarios of supervised classification. Conventional learning techniques adapt to such c…
Transitions from P to NP-hardness: the case of the Linear Ordering Problem
Anne Elorza, Leticia Hernando, Jose A. Lozano
In this paper we evaluate how constructive heuristics degrade when a problem transits from P to NP-hard. This is done by means of the linear ordering problem. More specifically, fo…
When and How to Fool Explainable Models (and Humans) with Adversarial Examples
Jon Vadillo, Roberto Santana, Jose A. Lozano
Reliable deployment of machine learning models such as neural networks continues to be challenging due to several limitations. Some of the main shortcomings are the lack of interpr…
The EMPATHIC Project: Mid-term Achievements
M. I. Torres, J. M. Olaso, C. Montenegro +26
The goal of active aging is to promote changes in the elderly community so as to maintain an active, independent and socially-engaged lifestyle. Technological advancements currentl…
Analysis of Dominant Classes in Universal Adversarial Perturbations
Jon Vadillo, Roberto Santana, Jose A. Lozano
The reasons why Deep Neural Networks are susceptible to being fooled by adversarial examples remains an open discussion. Indeed, many different strategies can be employed to effici…
Probabilistic Load Forecasting Based on Adaptive Online Learning
Verónica Álvarez, Santiago Mazuelas, José A. Lozano
Load forecasting is crucial for multiple energy management tasks such as scheduling generation capacity, planning supply and demand, and minimizing energy trade costs. Such relevan…
A revisited branch-and-cut algorithm for large-scale orienteering problems
Gorka Kobeaga, María Merino, Jose A. Lozano
The orienteering problem is a route optimization problem which consists in finding a simple cycle that maximizes the total collected profit subject to a maximum distance limitation…
On Solving Cycle Problems with Branch-and-Cut: Extending Shrinking and Exact Subcycle Elimination Separation Algorithms
Gorka Kobeaga, María Merino, Jose A. Lozano
In this paper, we extend techniques developed in the context of the Travelling Salesperson Problem for cycle problems. Particularly, we study the shrinking of support graphs and th…
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions
Jon Vadillo, Roberto Santana, Jose A. Lozano
Despite the remarkable performance and generalization levels of deep learning models in a wide range of artificial intelligence tasks, it has been demonstrated that these models ca…
A review on outlier/anomaly detection in time series data
Ane Blázquez-García, Angel Conde, Usue Mori +1
Recent advances in technology have brought major breakthroughs in data collection, enabling a large amount of data to be gathered over time and thus generating time series. Mining…
Evolving Gaussian Process kernels from elementary mathematical expressions
Ibai Roman, Roberto Santana, Alexander Mendiburu +1
Choosing the most adequate kernel is crucial in many Machine Learning applications. Gaussian Process is a state-of-the-art technique for regression and classification that heavily…
Taxonomization of Combinatorial Optimization Problems in Fourier Space
Anne Elorza, Leticia Hernando, Jose A. Lozano
We propose and develop a novel framework for analyzing permutation-based combinatorial optimization problems, which could eventually be extended to other types of problems. Our app…
Sentiment analysis with genetically evolved Gaussian kernels
Ibai Roman, Alexander Mendiburu, Roberto Santana +1
Sentiment analysis consists of evaluating opinions or statements from the analysis of text. Among the methods used to estimate the degree in which a text expresses a given sentimen…
A data-driven approach to precipitation parameterizations using convolutional encoder-decoder neural networks
Pablo Rozas Larraondo, Luigi J. Renzullo, Inaki Inza +1
Numerical Weather Prediction (NWP) models represent sub-grid processes using parameterizations, which are often complex and a major source of uncertainty in weather forecasting. In…
Merge Non-Dominated Sorting Algorithm for Many-Objective Optimization
Javier Moreno, Daniel Rodriguez, Antonio Nebro +1
Many Pareto-based multi-objective evolutionary algorithms require to rank the solutions of the population in each iteration according to the dominance principle, what can become a…
A review on distance based time series classification
Amaia Abanda, Usue Mori, Jose A. Lozano
Time series classification is an increasing research topic due to the vast amount of time series data that are being created over a wide variety of fields. The particularity of the…
An efficient K -means clustering algorithm for massive data
Marco Capó, Aritz Pérez, Jose A. Lozano
The analysis of continously larger datasets is a task of major importance in a wide variety of scientific fields. In this sense, cluster analysis algorithms are a key element of ex…
Towards Competitive Classifiers for Unbalanced Classification Problems: A Study on the Performance Scores
Jonathan Ortigosa-Hernández, Iñaki Inza, Jose A. Lozano
Although a great methodological effort has been invested in proposing competitive solutions to the class-imbalance problem, little effort has been made in pursuing a theoretical un…
An efficient K-means algorithm for Massive Data
Marco Capó, Aritz Pérez, José Antonio Lozano
Due to the progressive growth of the amount of data available in a wide variety of scientific fields, it has become more difficult to ma- nipulate and analyze such information. Eve…
Computing factorized approximations of Pareto-fronts using mNM-landscapes and Boltzmann distributions
Roberto Santana, Alexander Mendiburu, Jose A. Lozano
NM-landscapes have been recently introduced as a class of tunable rugged models. They are a subset of the general interaction models where all the interactions are of order less or…
Mathematical Programming Strategies for Solving the Minimum Common String Partition Problem
Christian Blum, José A. Lozano, Pedro Pinacho Davidson
The minimum common string partition problem is an NP-hard combinatorial optimization problem with applications in computational biology. In this work we propose the first integer l…