Selection of negatives in Hopfield networks

In this work we propose a novel methodology for graph-based semi-supervised learning which is composed of two main steps: Step 1) a novel strategy for PU learning specific for Hopfield networks, which can be applied both to structured classes and to hierarchy-less contexts; Step 2) a semi-supervised classifier based on a family of parametric Hopfield networks, which embeds the negative selection performed at Step 1) in the dynamics of network.