High Order Neural Networks for Efficient Associative Memory Design
Abstract
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.
Cite
Text
Dreyfus et al. "High Order Neural Networks for Efficient Associative Memory Design." Neural Information Processing Systems, 1987.Markdown
[Dreyfus et al. "High Order Neural Networks for Efficient Associative Memory Design." Neural Information Processing Systems, 1987.](https://mlanthology.org/neurips/1987/dreyfus1987neurips-high/)BibTeX
@inproceedings{dreyfus1987neurips-high,
title = {{High Order Neural Networks for Efficient Associative Memory Design}},
author = {Dreyfus, Gérard and Guyon, Isabelle and Nadal, Jean-Pierre and Personnaz, Léon},
booktitle = {Neural Information Processing Systems},
year = {1987},
pages = {233-241},
url = {https://mlanthology.org/neurips/1987/dreyfus1987neurips-high/}
}