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Jeff Mahoney
Ph.D. Alumni
Email:
mahoney [at] firstadvisors com
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 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