Many algorithms for grammatical inference can be viewed as instances of a more general algorithm which maintains a set of primitive elements, which distributionally define sets of ...
This paper describes a novel intellectual structure for the subject space of material designed for selective autodidactic learning in a large knowledge base. This structure is base...
A few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process c...
In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. The estimate of P stands in some cl...
Abstract--This paper is focusing on exact Bayesian reasoning in systems of agents, which represent weakly coupled processing modules supporting collaborative inference through mess...