Capabilities of fallible FINite learning

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Capabilities of fallible FINite learning

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Annual Workshop on Computational Learning Theory archive
Proceedings of the sixth annual conference on Computational learning theory table of contents

Santa Cruz, California, United States

Pages: 199 - 208

Year of Publication: 1993

ISBN:0-89791-611-5

Authors

Robert Daley
Bala Kalyanasundaram
Mahendran Velauthapillai

Sponsors

SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 1, Downloads (12 Months): 12, Citation Count: 1

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Robert Daley, Transformation of probabilistic learning strategies into deterministic learning strategies, Proceedings of the first annual workshop on Computational learning theory, p.220-226, August 03-05, 1988, MIT, Cambridge, Massachusetts, United States
	2	Robert Daley , Bala Kalyanasundaram, Capabilities of probabilistic learners with bounded mind changes, Proceedings of the sixth annual conference on Computational learning theory, p.182-191, July 26-28, 1993, Santa Cruz, California, United States [doi>10.1145/168304.168329]
	3	R. Daley, and B. Kalyanasundaram, Use of reduction arguments in determining Popperian FINite learning capabilities, In preparation.
	4	Robert P. Daley , Bala Kalyanasundaram, Probabilistic and Pluralistic Learners with Mind Changes, Proceedings of the 17th International Symposium on Mathematical Foundations of Computer Science, p.218-226, August 24-28, 1992
	5	Robert Daley , Bala Kalyanasundaram , Mahendran Velauthapillai, Breaking the probability ½ barrier in FIN-type learning, Proceedings of the fifth annual workshop on Computational learning theory, p.203-217, July 27-29, 1992, Pittsburgh, Pennsylvania, United States [doi>10.1145/130385.130408]
	6	Robert Daley , Leonard Pitt , Mahendran Velauthapillai , Todd Will, Relations between probabilistic and team one-shot learners (extended abstract), Proceedings of the fourth annual workshop on Computational learning theory, p.228-239, August 05-07, 1991, Santa Cruz, California, United States
	7	R.V. Freivalds, Finite Identification of General Recursive Functions by Probabilistic Strategies, Akademie Verlag, Berlin, 1979.
	8	E.M. Gold, Language identification in the limit, Information and Control 10, 1967, 447-474.
	9	Sanjay Jain , Arun Sharma, Finite learning by a “team”, Proceedings of the third annual workshop on Computational learning theory, p.163-177, August 06-08, 1990, Rochester, New York, United States
	10	Daniel N. Osherson , Michael Stob , Scott Weinstein, Systems that learn: an introduction to learning theory for cognitive and computer scientists, MIT Press, Cambridge, MA, 1986
	11	L. Pitt, Probabilistic inductive inference, Journal of the ACM (JACM), v.36 n.2, p.383-433, April 1989 [doi>10.1145/62044.62053]
	12	Leonard Pitt , Carl H. Smith, Probability and plurality for aggregations of learning machines, Information and Computation, v.77 n.1, p.77-92, April 1988 [doi>10.1016/0890-5401(88)90046-6]
	13	Mahendran Velauthapillai, Inductive inference with bounded number of mind changes, Proceedings of the second annual workshop on Computational learning theory, p.200-213, December 1989, Santa Cruz, California, United States