We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
Human linguistic annotation is crucial for many natural language processing tasks but can be expensive and time-consuming. We explore the use of Amazon's Mechanical Turk syst...
Rion Snow, Brendan O'Connor, Daniel Jurafsky, Andr...
We extend a recently developed method [1] for learning the semantics of image databases using text and pictures. We incorporate statistical natural language processing in order to...
Word prediction performed by language models has an important role in many tasks as e.g. word sense disambiguation, speech recognition, hand-writing recognition, query spelling an...
Category ranking provides a way to classify plain text documents into a pre-determined set of categories. This work proposes to have a look at typical document collections and ana...