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Learning long sequences in binary neural networks

An original architecture of oriented sparse neural networks that enables the introduction of sequentiality in associative memories is proposed in this paper. This architecture can be regarded as a generalization of a recently proposed non oriented binary network based on cliques. Using a limited neuron resource, the network is able to learn very long sequences and to retrieve them only from the knowledge of some consecutive symbols.

@inproceedings{JiaGriBer20127,
  author = {Xiaoran Jiang and Vincent Gripon and
Claude Berrou},
  title = {Learning long sequences in binary neural
networks},
  booktitle = {Proceedings of Cognitive 2012},
  year = {2012},
  address = {Nice, France},
  pages = {165--170},
  month = {July},
}