Towards an effective multi-map self organizing recurrent neural network - CentraleSupélec
Communication Dans Un Congrès Année : 2014

Towards an effective multi-map self organizing recurrent neural network

Résumé

This paper presents a multi-map joint self-organizing architecture able to represent non-markovian temporal sequences. The proposed architecture is inspired by previous works based on dynamic neural fields. It provides a faster and easier to handle architecture making it easier to scale to higher dimensional machine learning problems.
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Dates et versions

hal-01104724 , version 1 (19-01-2015)

Identifiants

  • HAL Id : hal-01104724 , version 1

Citer

Denis Baheux, Jérémy Fix, Hervé Frezza-Buet. Towards an effective multi-map self organizing recurrent neural network. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2014, Bruges, Belgium. pp.201-206. ⟨hal-01104724⟩
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