This paper proposes a semi-supervised boosting approach to improve statistical word alignment with limited labeled data and large amounts of unlabeled data. The proposed approach ...
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
Recently, boosting is used widely in object detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifiers which is on...
Boosting is a remarkably simple and flexible classification algorithm with widespread applications in computer vision. However, the application of boosting to nonEuclidean, infini...
Recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifier...