— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sa...
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
Pattern matching is the most computation intensive task of a network intrusion detection system (NIDS). In this paper we present a hardware architecture to speed up the pattern mat...
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
While the trust paradigm is essential to broadly extend the communication between the environment’s actors, the evaluation of trust becomes a challenge when confronted with init...