High Order Neural Networks for Efficient Associative Memory Design

Dreyfus, Gérard, Guyon, Isabelle, Nadal, Jean-Pierre, Personnaz, Léon

Neural Information Processing Systems 

We propose learning rules for recurrent neural networks with high-order interactions between some or all neurons. The designed networks exhibit the desired associative memory function: perfect storage and retrieval of pieces of information and/or sequences of information of any complexity.

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