While existing learning techniques can be viewed as inducing programs from examples, most research has focused on rather narrow classes of programs, e.g., decision trees or logic ...
We have recently presented CarpeDiem, an algorithm that can be used for speeding up the evaluation of Supervised Sequential Learning (SSL) classifiers. CarpeDiem provides impress...
This paper describes a new learning by example mechanism and its application for digital circuit design automation. This mechanism uses finite state machines to represent the infer...
In this paper, when we use the term ontology, we are primarily referring to linked data in the form of RDF(S). The problem of ontology mapping has attracted considerable attention...
We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...