Jeff Mahoney
Ph.D. Alumni
Publications
Combining Symbolic and Connectionist Learning Methods to Refine Certainty-Factor Rule-Bases 1996
J. Jeffrey Mahoney, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 113 pages.
Comparing Methods For Refining Certainty Factor Rule-Bases 1994
J. Jeffrey Mahoney and Raymond J. Mooney, In Proceedings of the Eleventh International Workshop on Machine Learning (ML-94), pp. 173--180, Rutgers, NJ, July 1994.
Modifying Network Architectures For Certainty-Factor Rule-Base Revision 1994
J. Jeffrey Mahoney and Raymond J. Mooney, In Proceedings of the International Symposium on Integrating Knowledge and Neural Heuristics (ISIKNH-94), pp. 75--85, Pensacola, FL, May 1994.
Combining Connectionist and Symbolic Learning to Refine Certainty-Factor Rule-Bases 1993
J. Jeffrey Mahoney and Raymond J. Mooney, Connection Science (1993), pp. 339-364.
Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases 1992
J. Jeffrey Mahoney and Raymond J. Mooney, Advances in Neural Information Processing Systems (NIPS) (1992).
Combining Symbolic and Neural Learning to Revise Probabilistic Theories 1992
J. Jeffrey Mahoney and Raymond J. Mooney, In Proceedings of the ML92 Workshop on Integrated Learning in Real Domains, Aberdeen, Scotland, July 1992.
Labs
Formerly affiliated with Machine Learning