We present a new approach for mapping natural language sentences to their formal meaning representations using stringkernel-based classifiers. Our system learns these classifiers ...
This paper describes an empirical study to investigate the performance of a wide range of classifiers deployed in applications to classify biometric data. The study specifically re...
An efficient framework is proposed for the fast recovery of Bayesian network classifier. A novel algorithm, called Iterative Parent-Child learningBayesian Network Classifier (IPC-...
When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...
This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in...