Learning sparse messages in networks of neural cliques
  An extension to a recently introduced binary neural network is proposed in order to allow the learning of sparse messages, in large numbers and with high memory efficiency. This new network is justified both in biological and informational terms. The learning and retrieval rules are detailed and illustrated by various simulation results. 
Behrooz Kamary Aliabadi, Claude Berrou, Vincent Gripon and Xiaoran   Jiang
cs.NE