Haym Hirsh's Publications:
Applications in Computational Biology

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

• Daniel Kudenko and Haym Hirsh (1998).
  Feature Generation for Sequence Categorization.
  Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI98).
  AAAI Press/MIT Press.
• David Loewenstern, Helen Berman, and Haym Hirsh (1998).
  Maximum A Posteriori Classification of DNA Structure from Sequence Information.
  Proceedings of the Pacific Symposium on Biocomputing (PSB98).
• David Loewenstern, Haym Hirsh, Peter Yianilos, and Michiel Noordewier (1995).
  DNA Sequence Classification Using Compression-Based Induction.
  Rutgers University Computer Science Department Technical Report LCSR-TR-240, DIMACS Technical Report 95-04.
• Haym Hirsh and Michiel Noordewier (1994).
  Using Background Knowledge to Improve Inductive Learning: A Case Study in Molecular Biology.
  IEEE Expert, 9(5):3-6.
• Haym Hirsh and Nathalie Japkowicz (1994).
  Bootstrapping Training Data Representations for Inductive Learning: A Case Study in Molecular Biology.
  Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI94), pages 639-644.
  AAAI Press/MIT Press.
• Haym Hirsh and Michiel Noordewier (1994).
  Using Background Knowledge to Improve Inductive Learning of DNA Sequences.
  Proceedings of the Tenth IEEE Conference on Artificial Intelligence for Applications (CAIA94), pages 351-357.
  IEEE Computer Society Press.
• Nathalie Japkowicz and Haym Hirsh (1994).
  Towards a Bootstrapping Approach to Constructive Induction.
  Working Notes of the Workshop on Constructive Induction and Change of Representation, pages 27-32.
  Eleventh International Conference on Machine Learning (ICML94).