We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
We study the upgrading problem of existing Passive Optical Networks (PONs) that need to increase their capacity at different points in time. Our method upgrades line rates and migr...
M. De Andrade, Massimo Tornatore, S. Sallent, Bisw...
We compile Nova, a new language designed for writing network processing applications, using a back end based on integer-linear programming (ILP) for register allocation, optimal b...