Numerous statistical learning methods have been developed for visual recognition tasks. Few attempts, however, have been made to address theoretical issues, and in particular, stud...
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
In this paper, we discuss round robin classification (aka pairwise classification), a technique for handling multi-class problems with binary classifiers by learning one classifie...
For two-class datasets, we provide a method for estimating the generalization error of a bag using out-of-bag estimates. In bagging, each predictor (single hypothesis) is learned ...