This paper presents a new approach to discriminative modeling for classi cation and labeling. Our method, called Boosting on Multilevel Aggregates (BMA), adds a new class of hiera...
One of the major difficulties of handwriting recognition is the variability among symbols because of the different writer styles. In this paper we introduce the boosting of blurre...
We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-c...
Abstract. We focus on two recently proposed algorithms in the family of “boosting”-based learners for automated text classification, AdaBoost.MH and AdaBoost.MHKR . While the ...
Pio Nardiello, Fabrizio Sebastiani, Alessandro Spe...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...