We investigate improvements of AdaBoost that can exploit the fact that the weak hypotheses are one-sided, i.e. either all its positive (or negative) predictions are correct. In pa...
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Face representation based on the Visual Codebook becomes popular because of its excellent recognition performance, in which the critical problem is how to learn the most efficien...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...