We investigate temporal resolution of documents, such as determining the date of publication of a story based on its text. We describe and evaluate a model that build histograms e...
We use Wikipedia articles to semantically inform the generation of query models. To this end, we apply supervised machine learning to automatically link queries to Wikipedia artic...
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
This work investigates supervised word alignment methods that exploit inversion transduction grammar (ITG) constraints. We consider maximum margin and conditional likelihood objec...
Aria Haghighi, John Blitzer, John DeNero, Dan Klei...
This paper addresses the problem of learning archetypal structural models from examples. To this end we define a generative model for graphs where the distribution of observed nod...