Department of Computer Science

Machine Learning Research Group

University of Texas at Austin Artificial Intelligence Lab

Publications: 1996

  1. Inductive Logic Programming for Natural Language Processing
    [Details] [PDF]
    Raymond J. Mooney
    In Stephen Muggleton, editors, Inductive Logic Programming: Selected papers from the 6th International Workshop, 3-22, Berlin, 1996. Springer Verlag.
  2. Integrating Explanation-Based and Inductive Learning Techniques to Acquire Search-Control for Planning
    [Details] [PDF]
    Tara A. Estlin
    Technical Report AI96-250, Department of Computer Sciences, University of Texas, Austin, TX, 1996.
  3. Learning to Parse Database Queries using Inductive Logic Programming
    [Details] [PDF]
    John M. Zelle and Raymond J. Mooney
    In AAAI/IAAI, 1050-1055, Portland, OR, August 1996. AAAI Press/MIT Press.
  4. A Novel Application of Theory Refinement to Student Modeling
    [Details] [PDF]
    Paul Baffes and Raymond J. Mooney
    In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 403-408, Portland, OR, August 1996.
  5. Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes
    [Details] [PDF]
    Siddarth Subramanian and Raymond J. Mooney
    In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 965-970, Portland, OR, August 1996.
  6. Multi-Strategy Learning of Search Control for Partial-Order Planning
    [Details] [PDF]
    Tara A. Estlin and Raymond J. Mooney
    In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 843-848, Portland, OR, August 1996.
  7. Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning
    [Details] [PDF]
    Raymond J. Mooney
    In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-96), 82-91, Philadelphia, PA, 1996.
  8. Combining Symbolic and Connectionist Learning Methods to Refine Certainty-Factor Rule-Bases
    [Details] [PDF]
    J. Jeffrey Mahoney
    PhD Thesis, Department of Computer Sciences, University of Texas at Austin, May 1996. 113 pages.
  9. Integrating EBL and ILP to Acquire Control Rules for Planning
    [Details] [PDF]
    Tara A. Estlin and Raymond J. Mooney
    In Proceedings of the Third International Workshop on Multi-Strategy Learning (MSL-96), 271--279, Harpers Ferry, WV, May 1996.
  10. Refinement-Based Student Modeling and Automated Bug Library Construction
    [Details] [PDF]
    Paul Baffes and Raymond Mooney
    Journal of Artificial Intelligence in Education, 7(1):75-116, 1996.
  11. Revising Bayesian Network Parameters Using Backpropagation
    [Details] [PDF]
    Sowmya Ramachandran and Raymond J. Mooney
    In Proceedings of the International Conference on Neural Networks (ICNN-96), Special Session on Knowledge-Based Artificial Neural Networks, 82--87, Washington DC, June 1996.
  12. Corpus-Based Lexical Acquisition For Semantic Parsing
    [Details] [PDF]
    Cynthia Thompson
    February 1996. Ph.D. proposal.
  13. Lexical Acquisition: A Novel Machine Learning Problem
    [Details] [PDF]
    Cynthia A. Thompson and Raymond J. Mooney
    Technical Report, Artificial Intelligence Lab, University of Texas at Austin, January 1996.
  14. Advantages of Decision Lists and Implicit Negative in Inductive Logic Programming
    [Details] [PDF]
    Mary Elaine Califf and Raymond J. Mooney
    Technical Report, Artificial Intelligence Lab, University of Texas at Austin, January 1996.
  15. Comparative Results on Using Inductive Logic Programming for Corpus-based Parser Construction
    [Details] [PDF]
    John M. Zelle and Raymond J. Mooney
    In Stefan Wermter and Ellen Riloff and Gabriela Scheler, editors, Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, 355-369, Berlin, 1996. Springer.
  16. Learning the Past Tense of English Verbs Using Inductive Logic Programming
    [Details] [PDF]
    Raymond J. Mooney and Mary Elaine Califf
    In {S. Wermter, E. Riloff} and G. Scheler, editors, Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, 370-384, Berlin, 1996. Springer.
  17. Hybrid Learning of Search Control for Partial-Order Planning
    [Details] [PDF]
    Tara A. Estlin and Raymond J. Mooney
    In Malik Ghallab and Alfredo Milani, editors, New Directions in AI Planning, 129-140, Amsterdam, 1996. IOS Press.