Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Abstract—Product-line architectures (PLAs) designed for mobile devices create a unique challenge for automated product variant selection engines since variants must be derived on...
Jules White, Douglas C. Schmidt, Egon Wuchner, And...
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
Abstract. We address the problem of joint feature selection in multiple related classification or regression tasks. When doing feature selection with multiple tasks, usually one c...
Paramveer S. Dhillon, Brian Tomasik, Dean P. Foste...