Increasing the Capacity of a Hopfield Network without Sacrificing Functionality

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Neural Networks and Deep Learning (2018, unknown): “The Storkey learning rule is proposed in [471].”
Catastrophic Forgetting and the Pseudorehearsal Solution in Hopfield-type Networks (1998, background): “The pseudo inverse (Hertz, Krough, and Palmer, 1991; Storkey, 1997) learning rule is an example of a non-local learning procedure.”
On the Origin of Deep Learning (2017, methodology): “As follow-ups of the invention of Hopfield Network, many works are attempted to study and increase the capacity of original Hopfield Network (Storkey, 1997; Liou and Yuan, 1999; Liou and Lin, 2006).”
Machine learning \& artificial intelligence in the quantum domain (2017, background): “This, and other properties of a useful storing rule, that is, rule which specifies W given the patterns, are given as follows (Storkey, 1997): a) locality: an update of a particular connection should depend only on the information available to the neurons on either side of the connection96; b) incre”