As the data for more and more languages is finding its way into digital form, with an increasing amount of this data being posted to the Web, it has become possible to collect lan...
In this paper, we examine on-line learning problems in which the target concept is allowed to change over time. In each trial a master algorithm receives predictions from a large ...
This paper focuses on the detection of objects with Lambertian surface under both varying dlumination and pose We offer to apply a novel detection method that proceeds by modeling...
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Abstract. A large experiment on combining classifiers is reported and discussed. It includes, both, the combination of different classifiers on the same feature set and the combina...