One problem with using CBR for diagnosis is that a full case description may not be available at the beginning of the diagnosis. The standard CBR methodology requires a detailed c...
We present a new method for the incremental training of multiclass Support Vector Machines that provides computational efficiency for training problems in the case where the trai...
Incremental parsing techniques such as shift-reduce have gained popularity thanks to their efficiency, but there remains a major problem: the search is greedy and only explores a ...
In this paper, we extend the traditional formalization of a Distributed Constraint Satisfaction Problems (DisCSP) to a Quantified DisCSP. A Quantified DisCSP includes several unive...
Abstract— Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrai...