Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...
In this paper we describe preliminary work that examines whether statistical properties of the structure of websites can be an informative measure of their quality. We aim to deve...
Vaclav Petricek, Tobias Escher, Ingemar J. Cox, He...
Comparative evaluation of visualization and experiment results is a critical step in computational steering. In this paper, we present a study of image comparison metrics for quan...
We propose a multiple classifier system approach to object recognition in computer vision. The aim of the approach is to use multiple experts successively to prune the list of cand...