Machine learning of limit programs (i.e., programs allowed finitely many mind changes about their legitimate outputs) for computable functions is studied. Learning of iterated lim...
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Most connectionist research has focused on learning mappings from one space to another (eg. classification and regression). This paper introduces the more general task of learnin...
We evaluate two broad classes of cognitive mechanisms that might support the learning of sequential patterns. According to the first, learning is based on the gradual accumulation...
Constraint Logic Programming (CLP) and Abductive Logic Programming (ALP) share the important concept of conditional answer. We exploit their deep similarities to implement an effic...
Marco Gavanelli, Evelina Lamma, Paola Mello, Miche...