Journal Articles
Disambiguating Highly Ambiguous Words, with E. Voorhees. Computational Linguistics 24:125--145, 1998.
Knowledge-Based Artificial Neural Networks, with J.W. Shavlik. Artificial Intelligence, 70:119--165, 1994.
The Extraction of Refined Rules from Knowledge-Based Neural Networks, with J.W. Shavlik. Machine Learning, 13:71--101, 1993.
Using Neural Networks to Refine Biological Knowledge, with J.W. Shavlik and M.O. Noordewier. International Journal of Genome Research, 1:81--107, 1992.
Symbolic and neural net learning algorithms: An empirical comparison, with J.W. Shavlik, R.J. Mooney. Machine Learning, 6:111--143, 1991.
An approach to combining explanation-based and neural learning algorithms, with J.W. Shavlik. Connection Science: The Journal of Neural Computing, Artificial Intelligence, and Cognitive Research, 1:233--255, 1990. (Also appears in Readings in Machine Learning, Morgan Kaufmann, 1990 and Applications of Learning and Planning Methods, World Scientific, 1991.
Book Chapters
Supervised Learning using Unclassified and Classified Examples. In Computational Learning Theory and Natural Learning Systems 4, R. Greiner, T. Petsche and S.J. Hanson (eds.), MIT Press, 1997.
Towards Building Contextual Representations of Word Senses Using Statistical Models, with C. Leacock and E. M. Voorhees. In Corpus Processing for Lexical Acquisition, B. Boguraev and J. Pustejovsky (eds.), MIT Press, 1996.
A Knowledge-Based Model of Geometry Learning, with R. Lehrer. In Computational Learning Theory and Natural Learning Systems 3, T. Petsche, S.J. Hanson and J. Shavlik (eds.), MIT Press, 1995.
Learning Context to Disambiguate Word Senses, with E. Voorhees and C. Leacock. In Computational Learning Theory and Natural Learning Systems 3, T. Petsche, S.J. Hanson and J. Shavlik (eds.), MIT Press, 1995.
Using Knowledge-Based Neural Networks to Refine Roughly-Correct Information, with J.W. Shavlik. In Computational Learning Theory and Natural Learning Systems 2, T. Petsche, S.J. Hanson, M. Kearns and R.L. Rivest (eds.), MIT Press, 1994.
Refining Symbolic Knowledge Using Neural Networks, with J.W. Shavlik. In Machine Learning: An Artificial Intelligence Approach, volume 4, R. Michalski and G. Tecuci (eds.), Morgan Kaufmann, 1993.
Hybrid Symbolic-Neural Methods for Improved Recognition Using High-Level Visual Features, with J.W. Shavlik. In Neural Networks for Human and Machine Perception, H. Wechsler (ed.), Academic Press, 1991.
Conference Proceedings
Local Expert Autoassociators for Anomaly Detection. In Proceedings of the Seventeenth International Conference on Machine Learning. Stanford, CA. 2000.
Learnig Priorities from Noisy Examples, with Thomas Petsche and Michael R. Miller. In Proceedings of the Seventeenth International Conference on Machine Learning. Stanford, CA. 2000.
Using Unlabeled Data for Supervised Learning. In Advances in Neural Information Processing Systems 8, Denver, Co, 1995.
Learning Collection Fusion Strategies for Information Retrieval, with E. Voorhees, N. K. Gupta and B. Johnson-Laird. In Proceedings of the Twelfth International Machine Learning Conference, Tahoe City, CA, 1995.
A Patient-Adaptive Neural-Network ECG Patient Monitoring Algorithm, with R. Watrous. In Computers in Cardiology, Vienna, 1995.
Synthesize, optimize, analyze, repeat (SOAR): Application of neural network tools to ECG patient monitoring, with R. Watrous, M. Glassman, M. Shahraray and D. Theivanayagam. In Proceedings of the Third International Congress on Air- and Structure-Borne Sound and Vibration, Montreal, 1994.
Towards Building Contextual Representations of Word Senses Using Statistical Models, with C. Leacock and E. M. Voorhees. In Proceedings of SIGLEX Workshop: Acquisition of Lexical Knowledge from Text, 1993.
Corpus-Based Statistical Sense Resolution, with C. Leacock and E. M. Voorhees. In Proceedings of the ARPA Workshop on Human Language Technology, Princeton, NJ, 1993.
A Knowledge-Based Model of Geometry Learning, with R. Lehrer. In Advances in Neural Information Processing Systems 5, Denver, CO, 1992.
Using Symbolic Learning to Improve Knowledge-Based Neural Networks, with J. W. Shavlik. In Proceedings of the Tenth National Conference on Artificial Intelligence, San Jose, CA, 1992.
Refining Symbolic Knowledge Using Neural Networks, with J. W. Shavlik. In Proceedings of the International Workshop on Multistrategy Learning, Harpers Ferry, WV, 1991.
Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules, with J. W. Shavlik. In Advances in Neural Information Processing Systems 4, Denver, CO, 1991.
Constructive Induction using Knowledge-Based Neural Networks, with M. W. Craven and J. W. Shavlik. In Proceedings of the Eighth International Machine Learning Workshop, Chicago, IL, 1991.
Training knowledge-based neural networks to recognize genes in DNA sequences, with M. O. Noordewier and J. W. Shavlik. In Advances in Neural Information Processing Systems 3, Denver, CO, 1990.
Refinement of approximate domain theories by knowledge-based artificial neural networks, with M. O. Noordewier and J. W. Shavlik. In Proceedings of the Eighth National Conference on Artificial Intelligence, Boston, MA, 1990.
Learning to recognize promoters in DNA sequences, with M. O. Noordewier and J. W. Shavlik. In Proceedings of the AAAI Symposium on Artificial Intelligence and Molecular Biology, Stanford, CA, 1990.
An experimental comparison of symbolic and connectionist learning algorithms, with R. J. Mooney, J. W. Shavlik, and A. Gove. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI, 1989.
Processing issues in comparisons of symbolic and connectionist learning systems, with D. Fisher, K. McKusick, R. J. Mooney, and J. W. Shavlik. In Proceedings of the Sixth International Workshop on Machine Learning, Ithaca, NY, 1989.
Combining explanation-based learning and artificial neural networks, with J. W. Shavlik. In Proceedings of the Sixth International Workshop on Machine Learning, Ithaca, NY, 1989.