Haym Hirsh's Publications:
Other Applications

Some papers can be viewed by clicking on their titles.
(A few more still need to be put on-line.)

• Haym Hirsh and Steven Chien (2001).
  Proceedings of the Thirteenth Conference on Innovative Applications of Artificial Intelligence.
  AAAI Press/MIT Press.
• Robert Engelmore and Haym Hirsh (2001).
  The Twelfth Innovative Applications of Artificial Intelligence Conference (IAAI-2001).
  AI Magazine, 22(2):13-14.
• Gary M. Weiss and Haym Hirsh (2000).
  Learning to Predict Extremely Rare Events.
  Working Notes of the Workshop on Learning from Imbalanced Data Sets,
  The Seventeenth National Conference on Artificial Intelligence (AAAI-2000).
• Gary M. Weiss and Haym Hirsh (1998).
  Learning to Predict Rare Events in Categorical Times-Series Data.
  Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD98).
  AAAI Press/MIT Press.
• Gary M. Weiss and Haym Hirsh (1998).
  Learning to Predict Rare Events in Categorical Time-Series Data.
  Working Notes of the Joint Workshop on Predicting the Future: AI Approaches to Time Series Analysis, Fifteenth National Conference on Artificial Intelligence (AAAI98)/Fifteenth International Conference on Machine Learning (ICML98).
  AAAI Press.
• Arunava Banerjee, Haym Hirsh, and Thomas Ellman (1995).
  Inductive Learning of Feature Tracking Rules for Scientific Visualization.
  Working Notes of the Workshop on Machine Learning in Engineering.
  Fourteenth International Joint Conference on Artificial Intelligence (IJCAI95).
  (Also Rutgers University Computer Science Department Technical Report HPCD-TR-29.)
• Haym Hirsh, Thomas Ellman, Arunava Banerjee, David Drischel, Hongbing Yao, and Norman Zabusky (1995).
  Reduced Model Formation for 2D Vortex Interactions Using Machine Learning.
  Working Notes of the AAAI Spring Symposium on Systematic Methods of Scientific Discovery.
• Haym Hirsh (1990).
  Incremental Version-Space Merging: A General Framework for Concept Learning.
  Foreword by Tom M. Mitchell.
  Kluwer Academic Publishers.
• Derek Sleeman, Haym Hirsh, Ian Ellery, and In-Yung Kim (1990).
  Extending Domain Theories: Two Case Studies in Student Modeling.
  Machine Learning, 5(1):11-37.
• Haym Hirsh (1989).
  Incremental Version Space Merging: A General Framework for Concept Learning.
  Stanford University Computer Science Department Technical Report (Ph.D. Dissertation).
• Scott H. Clearwater, Tze-Pin Cheng, Haym Hirsh, and Bruce G. Buchanan (1989).
  Incremental Batch Learning.
  Proceedings of the Sixth International Machine Learning Workshop, pages 366-370.
  Morgan Kaufmann Publishers.