Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative...
Thomas L. Griffiths, Mark Steyvers, David M. Blei,...
We present a unified model of what was traditionally viewed as two separate tasks: data association and intensity tracking of multiple topics over time. In the data association pa...
The paper presents an approach to the task of automatic document categorization in the field of economics. Since the documents can be annotated with multiple keywords (labels), we ...
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...