This paper describes an empirical study of high-performance dependency parsers based on a semi-supervised learning approach. We describe an extension of semisupervised structured ...
Jun Suzuki, Hideki Isozaki, Xavier Carreras, Micha...
A significant portion of the world's text is tagged by readers on social bookmarking websites. Credit attribution is an inherent problem in these corpora because most pages h...
Daniel Ramage, David Hall, Ramesh Nallapati, Chris...
We present a model-driven approach to the segmentation of nasal cavity and paranasal sinus boundaries. Based on computed tomography data of a patients head, our approach aims to ex...
Carsten Last, Simon Winkelbach, Friedrich M. Wahl,...
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
: In the present paper we address the problem of computing the Minimal Additional Sensor Sets (MASS) that guarantee a desired level of diagnostic discrimination for a system. Recen...