109 citations · 709 across the 84 of their papers we have counts for
8 papers · 1 filter
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…
Parallelized Tensor Train Learning of Polynomial Classifiers
Zhongming Chen, Kim Batselier, Johan A. K. Suykens +1
In pattern classification, polynomial classifiers are well-studied methods as they are capable of generating complex decision surfaces. Unfortunately, the use of multivariate polyn…
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…
Kernel Density Estimation for Dynamical Systems
Hanyuan Hang, Ingo Steinwart, Yunlong Feng +1
We study the density estimation problem with observations generated by certain dynamical systems that admit a unique underlying invariant Lebesgue density. Observations drawn from…
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…