My Publications

• Additional publications related to Maximum Margin Matrix Factorization
• Code for Fast MMMF

2007

• Extracting Information from Informal Communication. [PDF]
  Read the introduction: Postscript, PDF
  Jason D. M. Rennie.
  Massachusetts Institute of Technology. Ph.D. Thesis. February, 2007.
  Committee: Tommi Jaakkola, Michael Collins, Tomaso Poggio.

2005

• Loss Functions for Preference Levels: Regression with Discrete Ordered Labels. [PDF]
  Jason D. M. Rennie and Nathan Srebro.
  Proceedings of the IJCAI Multidisciplinary Workshop on Advances in Preference Handling. 2005.
• Fast Maximum Margin Matrix Factorization for Collaborative Prediction. [PDF]
  Jason D. M. Rennie and Nathan Srebro.
  Proceedings of the 22nd International Conference on Machine Learning (ICML). 2005.
• Using Term Informativeness for Named Entity Detection. [PDF]
  Jason D. M. Rennie and Tommi Jaakkola.
  Proceedings of the 28th Annual Conference on Research and Development in Information Retrieval (SIGIR). 2005.
  
• Maximum-Margin Matrix Factorization. [PDF]
  Nathan Srebro, Jason D. M. Rennie and Tommi Jaakkola.
  Advances in Neural Information Processing Systems 17 (NIPS). 2005.

2004

• TopCat: Data mining for topic identification in a text corpus. [PDF]
  Chris Clifton, Robert Cooley and Jason Rennie.
  Transactions on Knowledge and Data Engineering 16(8), IEEE Computer Society Press, August, 2004.

2003

• Tackling the Poor Assumptions of Naive Bayes Text Classifiers. [PDF]
  Jason D. M. Rennie, Lawrence Shih, Jaime Teevan and David R. Karger.
  Proceedings of the Twentieth International Conference on Machine Learning (ICML). 2003.
• Text Bundling: Statistics-Based Data Reduction. [PDF]
  Lawrence Shih, Jason D. M. Rennie, Yu-Han Chang and David R. Karger.
  Proceedings of the Twentieth International Conference on Machine Learning (ICML). 2003.
  This paper applies a similar idea. Their technique is more general, but ours is efficient for high-dimensional data such as text.

2002

• Not Too Hot, Not Too Cold: The Bundled-SVM is Just Right! [PDF]
  Lawrence Shih, Yu-Han Chang, Jason D. M. Rennie and David Karger.
  Proceedings of the ICML-2002 Workshop on Text Learning. 2002.

2000

• Automating the Construction of Internet Portals with Machine Learning. [PDF]
  Andrew McCallum, Kamal Nigam, Jason Rennie and Kristie Seymore.
  Information Retrieval Journal. Volume 3, pgs. 127-163. Kluwer. 2000.
• ifile: An Application of Machine Learning to E-mail Filtering. [PDF]
  Jason D. M. Rennie.
  Proceedings of the KDD-2000 Workshop on Text Mining. 2000.

1999

• Using Reinforcement Learning to Spider the Web Efficiently. [PDF]
  Jason Rennie and Andrew McCallum.
  Proceedings of the Sixteenth International Conference on Machine Learning (ICML). 1999.
  Links are to Text Data Analysis workshop version with new results
• A Machine Learning Approach to Building Domain-Specific Search Engines. [PDF]
  Andrew McCallum, Kamal Nigam, Jason Rennie and Kristie Seymore.
  Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI). 1999.
• Building Domain-Specific Search Engines with Machine Learning Techniques. [PDF]
  Andrew McCallum, Kamal Nigam, Jason Rennie and Kristie Seymore.
  Proceedings of the AAAI-99 Spring Symposium. 1999.

Non-Peer-Reviewed Publications

• Automatic Feature Induction for Text Classification. [PDF]
  Jason D. M. Rennie and Tommi Jaakkola.
  MIT AI Lab Abstract Book. 2002.
• Improving Multiclass Text Classification with the Support Vector Machine. [PDF]
  Jason D. M. Rennie and Ryan Rifkin.
  Massachusetts Institute of Technology. AI Memo AIM-2001-026. 2001.
• Improving Multi-class Text Classification with Naive Bayes. [PDF]
  Jason D. M. Rennie.
  Master's Thesis. Massachusetts Institute of Technology. AI Technical Report AITR-2001-004. 2001.
• Another Sys Called Qanda. [PDF]
  E. Breck, J. Burger, L. Ferro, W. Greiff, M. Light, I. Mani, J. Rennie.
  NIST Special Publication 500-249: The Ninth Text REtrieval Conference (TREC 9). 2001.

NOTE: Some of the older PDF's do not have figures.

How not to write a computer science research paper.

The DBLP has citations for a very large number of computer science research papers.