• DOI:10.1007/s13218-012-0207-2
Corpus ID: 13923011

Neural Networks for Complex Data

@article{Cottrell2012NeuralNF,
  title={Neural Networks for Complex Data},
  author={M. Cottrell and M. Olteanu and F. Rossi and J. Rynkiewicz and N. Villa-Vialaneix},
  journal={KI - K{\"u}nstliche Intelligenz},
  year={2012},
  volume={26},
  pages={373-380}
}

M. Cottrell, M. Olteanu, +2 authors N. Villa-Vialaneix

Published 2012

Computer Science, Mathematics

KI - Künstliche Intelligenz

View on Springer

arxiv.org

Save to Library

Create Alert

Cite

Launch Research Feed

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 Université Paris 1.