Large vocabulary speech recognition systems fail to recognize words beyond their vocabulary, many of which are information rich terms, like named entities or foreign words. Hybrid...
Carolina Parada, Mark Dredze, Abhinav Sethy, Ariya...
We extend the classical single-task active learning (AL) approach. In the multi-task active learning (MTAL) paradigm, we select examples for several annotation tasks rather than f...
Roi Reichart, Katrin Tomanek, Udo Hahn, Ari Rappop...
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
The primary purpose of news articles is to convey information about who, what, when and where. But learning and summarizing these relationships for collections of thousands to mil...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...
We present a simple and scalable algorithm for clustering tens of millions of phrases and use the resulting clusters as features in discriminative classifiers. To demonstrate the ...