Haym Hirsh's Publications:
Version Spaces

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

• Haym Hirsh, Nina Mishra, and Leonard Pitt (2004)
  Version Spaces and the Consistency Problem.
  Artificial Intelligence 156(2):115-138.
• Haym Hirsh, Nina Mishra, and Leonard Pitt (1997).
  Version Spaces Without Boundary Sets.
  Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI97).
  AAAI Press/MIT Press.
• Haym Hirsh (1994).
  Generalizing Version Spaces.
  Machine Learning, 17(1):5-45.
• Haym Hirsh and William W. Cohen (1994).
  Learning from Data with Bounded Inconsistency: Theoretical and Experimental Results.
  In S. Hanson, G. Drastal, and R. Rivest, editors, Computational Learning Theory and Natural Learning Systems, Constraints and Prospects, pages 355-380.
  MIT Press.
• Steven W. Norton and Haym Hirsh (1993).
  Learning DNF Via Probabilistic Evidence Combination.
  Proceedings of the Tenth International Conference on Machine Learning (ICML93), pages 220-227.
  Morgan Kaufmann Publishers.
• Paul S. Rosenbloom, Haym Hirsh, William W. Cohen, and Benjamin D. Smith (1993).
  Two Frameworks for Integrating Knowledge in Induction.
  Proceedings of the Seventh Annual Workshop on Space Operations, Applications and Research, pages 226-233.
  NASA Conference Publication 3240.
• Haym Hirsh (1992).
  Polynomial-Time Learning with Version Spaces.
  Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI92), pages 117-122.
  AAAI Press/MIT Press.
• Steven W. Norton and Haym Hirsh (1992).
  Classifier Learning from Noisy Data as Probabilistic Evidence Combination.
  Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI92), pages 141-146.
  AAAI Press/MIT Press.
• Haym Hirsh (1992).
  The Computational Complexity of the Candidate-Elimination Algorithm.
  Rutgers University Computer Science Department Technical Report ML-TR-36.
• Haym Hirsh (1991).
  Theoretical Underpinnings of Version Spaces.
  Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI91), pages 665-670.
  Morgan Kaufmann Publishers.
• Steven W. Norton and Haym Hirsh (1991).
  Classifier Learning from Noisy Data as Reasoning Under Uncertainty.
  Rutgers University Computer Science Department Technical Report ML-TR-34.
• Haym Hirsh (1990).
  Incremental Version-Space Merging: A General Framework for Concept Learning.
  Foreword by Tom M. Mitchell.
  Kluwer Academic Publishers.
• Haym Hirsh (1990).
  Incremental Version-Space Merging.
  Proceedings of the Seventh International Conference on Machine Learning (ICML90), pages 330-338.
  Morgan Kaufmann Publishers.
• Haym Hirsh (1990).
  Learning from Data with Bounded Inconsistency.
  Proceedings of the Seventh International Conference on Machine Learning (ICML90), pages 32-39.
  Morgan Kaufmann Publishers.
• Haym Hirsh (1990).
  Knowledge As Bias.
  In D.P. Benjamin, editor, Change of Representation and Inductive Bias, pages 209-221.
  Kluwer Academic Publishers.
• Haym Hirsh (1989).
  Incremental Version Space Merging: A General Framework for Concept Learning.
  Stanford University Computer Science Department Technical Report (Ph.D. Dissertation).
• Haym Hirsh (1989).
  Combining Empirical and Analytical Learning with Version Spaces.
  Proceedings of the Sixth International Machine Learning Workshop, pages 29-33.
  Morgan Kaufmann Publishers.