Neural Networks for Complex Data
Neural and Evolutionary Computing
2012-10-26 v1 Machine Learning
Machine Learning
Abstract
Artificial neural networks are simple and efficient machine learning tools. Defined originally in the traditional setting of simple vector data, neural network models have evolved to address more and more difficulties of complex real world problems, ranging from time evolving data to sophisticated data structures such as graphs and functions. This paper summarizes advances on those themes from the last decade, with a focus on results obtained by members of the SAMM team of Universit\'e Paris 1
Cite
@article{arxiv.1210.6511,
title = {Neural Networks for Complex Data},
author = {Marie Cottrell and Madalina Olteanu and Fabrice Rossi and Joseph Rynkiewicz and Nathalie Villa-Vialaneix},
journal= {arXiv preprint arXiv:1210.6511},
year = {2012}
}