``Text Learning: Beyond Supervision''

A workshop at IJCAI'2001
. August 6, 2001

Due to the rapidly increasing amount of textual data available and the range of interesting and important problems arising in text analysis, there has been growing interest in applying machine learning methods to text. There has also been significant recent interest in research that combines supervised and unsupervised learning. This research is especially relevant to text learning because the inherent complexity of natural language usually requires models with many parameters: estimating those parameters requires a lot of data, and obtaining labeled data is difficult and expensive. By combining unsupervised learning with supervised learning, the need for labeled training data can often be greatly reduced, allowing for the development of more powerful models and methods.

The workshop will explore machine learning methods for solving supervised text learning tasks that exploit training methods beyond straightforward supervised learning.

Relevant topics include:

The last several years have seen many disparate innovations in the intersection between text learning and the combination of supervised and unsupervised learning. The goal of this workshop is to bring together researchers from the machine learning, information retrieval, computational linguistics and language modeling to talk about their different perspectives on this intersection and to share their latest ideas.

Schedule and Papers

Invited Speakers

David Yarowsky
Assistant Professor
Department of Computer Science
Johns Hopkins University

Tommi Jaakkola
Assistant Professor
Department of Computer Science
Massachusetts Institute of Technology

Important Dates

FridayMar 23 2001Paper submissions due
FridayApr 06 2001Acceptance notification
FridayApr 20 2001Camera ready papers due

Submission Procedure

Authors are asked to prepare a paper in Postscript or PDF format. Submissions should conform to the IJCAI-2001 format, and be 8 pages or less. We encourage submissions containing original theoretical and applied concepts. Experimental results are also encouraged, even if they are only preliminary. To submit a paper, email it to before 6pm on the day of the deadline.

Formatting instructions can be found here.

Organizing Committee

Andrew McCallum
  WhizBang Labs - Research, 4616 Henry Street, Pittsburgh, PA  15218
  T: 412-683-9132 F: 412-683-4436

Kamal Nigam
  School of Computer Science, Carnegie Mellon, Pittsburgh, PA 15213
  T: 412-268-3070 F: 412-268-5576

Tony Jebara
  MIT, Media Laboratory - 20 Ames Street, E15-390, Cambridge, MA 02138
  T: 617-253-0326 F: 617-253-8874

Lillian Lee
  Department of Computer Science, Cornell University, Ithaca, NY 14853
  T: 607-255-8119 F: 607-255-4428

Andrew McCallum
Last modified: Tue Jul 24 14:29:58 EDT 2001