The goal of text categorization is to classify documents into a certain number of pre-defined categories. The previous works in this area have used a large number of labeled train...
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning al...
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
The emergence of the world-wide-web has led to an increased interest in methods for searching for information. A key characteristic of many of the online document collections is t...