Davis, R.; Frawley, W.; Austin, H.; Carlbom, I.; Pruchnik, P.; Sneiderman, R.; and Gilreath, J. 1981. The Dipmeter Advisor: Interpretation of Geologic Signals. Proceedings of the Seventh International Joint Conference on Artificial Intelligence, 846-849. Menlo Park, Calif.: International Joint Conferences on Artificial Intelligence.
Frawley, W., and Goyal, S. 1984. Artificial Intelligence Research Activities at GTE Laboratories. AI Magazine, 5(3):75-77.
Frawley, W., and Worrest, R. 1985. "Distributed Artificial Intelligence at GTE Laboratories'' in Report on the 1984 Distributed Artificial Intelligence Workshop. AI Magazine, 6(3):234-243.
Frawley, W. 1985. Computer Generation of Symbolic Generalized Inverses and Applications to Physics and Data Analysis. In Applications of Computer Algebra, ed. R. Pavelle, 415-426. Hingham, Mass.: Kluwer Academic Publishers.
Frawley, W. 1989. The Role of Simulation In Machine Learning Research. Proceedings of the Twenty-second Annual Simulation Symposium, 119-127. Washington, D.C.: IEEE Computer Society Press.
Piatetsky-Shapiro, G., and Frawley, W. eds. 1989. Proceedings of the IJCAI-89 Workshop on Knowledge Discovery in Databases. Waltham, Mass.: GTE Laboratories Incorporated.
Frawley, W. 1989. Using Functions To Encode Domain And Contextual Knowledge In Statistical Induction. Proceedings of the IJCAI-89 Workshop on Knowledge Discovery in Databases, 99-108. Waltham, Mass.: GTE Laboratories Incorporated.
Silver, B.; Vittal, J.; Frawley, W.; Iba, G.; and Bradford, K. 1990. ILS: A Framework for Integrating Multiple Heterogeneous Learning Agents. Proceedings of the Tenth International Workshop on Expert Systems and Their Applications, ed. J.-M. David, 301-313. Nanterre, France: EC2. (Conference Best Paper award)
Silver, B.; Frawley, W.; Iba, G.; Vittal, J.; and Bradford, K. 1990. ILS: A Framework for Multi-Paradigmatic Learning. Proceedings of the Seventh Annual Conference on Machine Learning, eds. B. Porter and R. Mooney, 348-356. San Mateo, Calif.: Morgan Kaufman.
Silver, B.; Frawley, W.; Iba, G.; and Vittal, J. 1991. An Architecture for Self-Improving Distributed Heterogeneous Agents. Proceedings of the Fourth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, ed. J. Bezdek, 275-283. Tullahoma, TN.: The University of Tennessee Space Institute.
Vittal, J.; Frawley, W.; Silver, B.; Iba, G.; and Doleac, J. 1991. An Architecture for Distributed, Adaptable Information Systems. Proceedings of the IJCAI-91 Workshop on Intelligent and Cooperative Information Systems, 99-110. Sydney, NSW: Australian National University Press.
Piatetsky-Shapiro, G., and Frawley, W. eds. 1991. Knowledge Discovery in Databases. Cambridge, Mass.: AAAI Press / The MIT Press.
Frawley, W.; Piatetsky-Shapiro, G.; and Matheus, C. 1991. Knowledge Discovery in Databases: An Overview. In Knowledge Discovery in Databases, eds. G. Piatetsky-Shapiro and W. Frawley, 1-27. Cambridge, Mass.: AAAI Press / The MIT Press.
Frawley, W. 1991. Using Functions To Encode Domain And Contextual Knowledge In Statistical Induction. In Knowledge Discovery in Databases, eds. G. Piatetsky-Shapiro and W. Frawley, 261-275. Cambridge, Mass.: AAAI Press / The MIT Press.
Frawley, W.; Piatetsky-Shapiro, G.; and Matheus, C. 1992. Knowledge Discovery in Databases: An Overview. AI Magazine, 13(3):57-70.
Vittal, J.; Frawley, W.; Silver, B.; Iba, G.; Fawcett, T.; Dusseault, S.; and Doleac, J. 1993. A Framework for Cooperative Adaptable Information Systems. In The Next Generation of Information Systems -- From Data To Knowledge, eds. M. P. Papazoglou and J. Zeleznikow. Springer-Verlag.
Silver, B.; Vittal, J.; Frawley, W.; Iba, G.; Fawcett, T.; Dusseault, S.; and Doleac, J. 1993. A Framework for Integrating Heterogeneous Learning Agents. In Second Generation Expert Systems, eds. J.-M. David, J.-P. Krivine, and R. Simmons, 746 - 764. Berlin: Springer-Verlag.
Vittal, J.; Silver, B.; Frawley, W.; Iba, G.; Fawcett, T.; Dusseault, S.; and Doleac, J. 1993. Intelligent and Cooperative Information Systems Meet Machine Learning. International Journal of Intelligent and Cooperative Information Systems, Vol. 1, No. 2.
Silver, B.; Frawley, W.; G. Iba and Vittal, J. 1993. ILS: A System of Learning Distributed Heterogeneous Agents for Network Traffic Management. In Proceedings of the International Conference on Communications, 1869-1874.
Adler, M., and Frawley, W. 1995. Learning Agents for Telecommunication. In Worldwide Intelligent Systems (Subtitle: Approaches to Telecommunications and Network Management), eds. J. Liebowitz and D. Prerau, 261-278. Amsterdam: IOS Press.
Computer Generation of Symbolic Generalized Inverses and Applications to Physics and Data Analysis. Symposium on Symbolic Algebraic Manipulation in Scientific Computation, 188th national meeting of the American Chemical Society. Philadelphia, Penn. August, 1984.
Can Computers Be Programmed to Learn? Fifth Annual Lester W. Strock Seminar, Museum of Fine Arts. Boston, Mass. October, 1984.
Machine Learning and Self-Improving Systems. Seminar on Artificial Intelligence, DPMA Education Foundation. Washington, DC. November, 1985.
The Artificial Intelligence Approach to the Study of Self-Improving Systems. Department of Computer Science, University of Hawaii. Honolulu, Hawaii. February, 1986.
Top-down Induction of Decision Trees. Department of Computer Science, Boston University. Boston, Mass. February, 1989.
The Role of Simulation In Machine Learning Research. Twenty-second Annual Simulation Symposium. Tampa, FL, March, 1989.
ILS: A Framework for Integrating Multiple Heterogeneous Learning Agents. Knowledge Systems Laboratory, Stanford University. Stanford, California. February, 1990.
ILS: A Framework for Integrating Multiple Heterogeneous Learning Agents. Departments of Electrical Engineering and Computer Science, University of Oklahoma. Norman, Oklahoma. February, 1990.
Function-Based Statistical Induction. Department of Mathematics Colloquium, University of Oklahoma. Norman, Oklahoma. February, 1990.
An Architecture for Self-Improving Distributed Heterogeneous Agents. Fourth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. Kauai, Hawaii. June, 1991.
Using Domain and Contextual Knowledge in Statistical Induction. Session on Symbolic Mathematics in Statistics, 151st annual meeting of the American Statistical Association. Atlanta, Georgia. August, 1991.
Knowledge Discovery In Databases. Session on Data Mining and Information Creation, Eighth Conference on Artificial Intelligence for Applications. Monterey, California. March, 1992.
Concept Learning and Knowledge Discovery. Instituto de Ciencias Matematicas de Sao Carlos, S.P., Brazil. December, 1992.
The Integrated Learning System and Knowledge Discovery in Databases. School of Electrical Engineering, Universidade Estadual de Campinas, S.P., Brazil. December, 1992.
The Integrated Learning System. Department of Computer Science, Universidade Federal de Florianopolis, S.C., Brazil. December, 1992.
The Role of AI in the Information Superhighway. Panel Member. Tenth IEEE Conference on Artificial Intelligence for Applications, San Antonio, March 1994.
Course taught: Machine Intelligence, graduate, four credit hours. Department of Industrial Engineering and Information Systems, Northeastern University. Spring, 1994.
W. Frawley, W. E. Kenyon, C. Y. Regat, F. F. Segesman, and J. Suau. Method of Generating Subsurface Characteristic Models. U.K. Patent No. 1405311 (to Schlumberger Ltd.).
W. Frawley and P. A. Mongeluzzo. Well-logging: Depth Correlation of Logs. U.S. Patent No. 4,320,469 (to Schlumberger Ltd.).
W. Frawley, Analysis of Gamma Ray Spectra for Determination of Selected Characteristics of an Unknown Material. Pending. Schlumberger file number 60.435.
Ultrasonic Absorption in Fluids. E. F. Carome, advisor. John Carroll University, 1958.
The Fundamentals of Digital Computers. E. F. Carome, advisor. John Carroll University, 1960.
Locally Disconjugate Families of Continuous Functions. W. T. Reid, advisor. University of Oklahoma, 1968.
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