3 papers
stat.ML2026
Manifold limit for the training of shallow graph convolutional neural networks
Johanna Tengler, Christoph Brune, José A. Iglesias
We study the discrete-to-continuum consistency of the training of shallow graph convolutional neural networks (GCNNs) on proximity graphs of sampled point clouds under a manifold a…
math.OC2025
Monotonicity of the jump set and jump amplitudes in one-dimensional TV denoising
Riccardo Cristoferi, Rita Ferreira, Irene Fonseca +1
We revisit the classical problem of denoising a one-dimensional scalar-valued function by minimizing the sum of an fidelity term and the total variation, scaled by a regulari…
cs.NE2021
A Multi-objective Evolutionary Algorithm for EEG Inverse Problem
José Enrique Alvarez Iglesias, Mayrim Vega-Hernández, Eduardo Martínez-Montes
In this paper, we proposed a multi-objective approach for the EEG Inverse Problem. This formulation does not need unknown parameters that involve empirical procedures. Due to the c…