High-performance computing clusters running longlived tasks currently cannot have kernel software updates applied to them without causing system downtime. These clusters miss oppo...
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
We present a framework that enables the use of traditional feature selection algorithms in a new context - for building a set of subsets of specified properties. During the course...
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...