We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
In this paper we present a technique for automatically generating constraints on parameter derivatives that reduce ambiguity in the behaviour prediction. Starting with a behaviour...
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of ins...