The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
We study the problem of object classification when training
and test classes are disjoint, i.e. no training examples of
the target classes are available. This setup has hardly be...
Christoph H. Lampert, Hannes Nickisch, Stefan Harm...
Abstract In many problems from different disciplines such as engineering, physics, medicine, and biology, a series of experimental data is used in order to generate a model that ca...
Georges K. Saharidis, Ioannis P. Androulakis, Mari...
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
Recently, there has been a flurry of research on face recognition based on multiple images or shots from either a video sequence or an image set. This paper is also such an attemp...