52 citations · 108 across the 6 of their papers we have counts for
8 papers
Fault Detection in Induction Motors using Functional Dimensionality Reduction Methods
María Barroso, José M. Bossio, Carlos M. Alaíz +1
The implementation of strategies for fault detection and diagnosis on rotating electrical machines is crucial for the reliability and safety of modern industrial systems. The contr…
Functional Diffusion Maps
María Barroso, Carlos María Alaíz, Ángela Fernández +1
Nowadays many real-world datasets can be considered as functional, in the sense that the processes which generate them are continuous. A fundamental property of this type of data i…
Faster SVM Training via Conjugate SMO
Alberto Torres-Barrán, Carlos Alaíz, José R. Dorronsoro
We propose an improved version of the SMO algorithm for training classification and regression SVMs, based on a Conjugate Descent procedure. This new approach only involves a modes…
Modified Frank-Wolfe Algorithm for Enhanced Sparsity in Support Vector Machine Classifiers
Carlos M. Alaíz, Johan A. K. Suykens
This work proposes a new algorithm for training a re-weighted L2 Support Vector Machine (SVM), inspired on the re-weighted Lasso algorithm of Candès et al. and on the equivalence b…
Robust Classification of Graph-Based Data
Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens
A graph-based classification method is proposed for semi-supervised learning in the case of Euclidean data and for classification in the case of graph data. Our manifold learning t…
Convex Formulation for Kernel PCA and its Use in Semi-Supervised Learning
Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens
In this paper, Kernel PCA is reinterpreted as the solution to a convex optimization problem. Actually, there is a constrained convex problem for each principal component, so that t…
Magnetic eigenmaps for community detection in directed networks
Michaël Fanuel, Carlos M. Alaíz, Johan A. K. Suykens
Communities in directed networks have often been characterized as regions with a high density of links, or as sets of nodes with certain patterns of connection. Our approach for co…
Magnetic Eigenmaps for the Visualization of Directed Networks
Michaël Fanuel, Carlos M. Alaíz, Ángela Fernández +1
We propose a framework for the visualization of directed networks relying on the eigenfunctions of the magnetic Laplacian, called here Magnetic Eigenmaps. The magnetic Laplacian is…