A unified variational methodology is developed for classification and clustering problems, and tested in the classification of tumors from gene expression data. It is based on flu...
J. P. Agnelli, M. Cadeiras, E. G. Tabak, C. V. Tur...
We specify the black box behavior of dataflow components by characterizing the relation between their input and their output histories. We distinguish between three main classes of...
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Dynamic program slicing is an effective technique for narrowing the errors to the relevant parts of a program when debugging. Given a slicing criterion, the dynamic slice contains...
We examine the stability of multi-class queueing systems with the special feature that the service rates of the various classes depend on the number of users present of each of th...