This paper proposes a novel Data Envelopment Analysis (DEA) based approach for model combination. We first prove that for the 2-class classification problems DEA models identify t...
This paper presents a method for classifying the direction of movement and for segmenting objects simultaneously using features of space-time patches. Our approach uses vector quan...
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Abstract. Recent findings in the domain of combining classifiers provide a surprising revision of the usefulness of diversity for modelling combined performance. Although there is ...
Traditional approaches to combining classifiers attempt to improve classification accuracy at the cost of increased processing. They may be viewed as providing an accuracy-speed tr...
Kumar Chellapilla, Michael Shilman, Patrice Simard