The e ciency of pattern recognition is particularly crucial in two scenarios; whenever there are a large number of classes to discriminate, and, whenever recognition must be perfo...
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
In this work we consider the task of relaxing the i.i.d. assumption in pattern recognition (or classification), aiming to make existing learning algorithms applicable to a wider r...
Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utiliz...
Themis P. Exarchos, Costas Papaloukas, Christos La...
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...