An Autoassociative Neural Network Model of Paired-Associate Learning

@article{Rizzuto2001AnAN,
title={An Autoassociative Neural Network Model of Paired-Associate Learning},
author={Daniel S. Rizzuto and Michael J. Kahana},
journal={Neural Computation},
year={2001},
volume={13},
pages={2075-2092}
}

Hebbian heteroassociative learning is inherently asymmetric. Storing a forward association, from item A to item B, enables recall of B (given A), but does not permit recall of A (given B). Recurrent networks can solve this problem by associating A to B and B back to A. In these recurrent networks, the forward and backward associations can be differentially weighted to account for asymmetries in recall performance. In the special case of equal strength forward and backward weights, these… CONTINUE READING