We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Decision lists (or ordered rule sets) have two attractive properties compared to unordered rule sets: they require a simpler classification procedure and they allow for a more co...
Abstract--We present an algorithm that coevolves fitness predictors, optimized for the solution population, which reduce fitness evaluation cost and frequency, while maintaining ev...
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Experimentation is one way to gain insight into how processes perform for a team, but industry teams rarely do experiments, fearing that such educational excursions will incur extr...