In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
We present an approach to classification of biomedical terms based on the information acquired automatically from the corpus of relevant literature. The learning phase consists of...
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
A variety of flexible models have been proposed to detect
objects in challenging real world scenes. Motivated
by some of the most successful techniques, we propose a
hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...