The aim of this work is to incorporate constraints into the partial evaluation procedure in order to obtain further specialisation through greater (constraint-based) information propagation. We incorporate constraints into the algorithm for the partial evaluation of the Escher language, a functional logic language based on rewriting. The preliminary implementation of the partial evaluator uses ...

We analyze URL and tag propagation on Twitter social network with 54 million nodes and 1.5 billion edges, one of the largest social networks studied in academia. We specifically focus on the interplay of external and network influences. We attribute propagation to the network whenever a user mentions a tag or URL after one of its neighbors has previously mentioned it, and to external influence ...

We study the behavior of untrained neural networks whose weights and biases are randomly distributed using mean field theory. We show the existence of depth scales that naturally limit the maximum depth of signal propagation through these random networks. Our main practical result is to show that random networks may be trained precisely when information can travel through them. Thus, the depth ...