In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing ...
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
We propose a novel, local feature-based face representation method based on twostage subset selection where the first stage finds the informative regions and the second stage ...
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...