FINite learning capabilities and their limits

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FINite learning capabilities and their limits

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

Nashville, Tennessee, United States

Pages: 81 - 89

Year of Publication: 1997

ISBN:0-89791-891-6

Authors

Robert Daley	Department of Computer Science, University of Pittsburgh, Pittsburgh, PA
Bala Kalyanasundaram	Department of Computer Science, University of Pittsburgh, Pittsburgh, PA

Sponsors

AT&T Labs :
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Vanderbilt University : Vanderbilt University

Publisher

ACM New York, NY, USA

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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	Rolf Wiehagen, Characterization Problems in the Theory of Inductive Inference, Proceedings of the Fifth Colloquium on Automata, Languages and Programming, p.494-508, July 17-21, 1978
	2	Rusins Freivalds. Finite identification of general recursive functions by probabilistic methods. In L. Budach, editor, Fundamentals of Computation Theory, pages 138-145. Akademie-Verlag, Berlin, 1979.
	3	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
	4	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
	5	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
	6	Robert Daly , Bala Kalyanasundaram , Mahendran Velauthapillai, Breaking the probability 12 barrier in FIN-type learning, Journal of Computer and System Sciences, v.50 n.3, p.574-599, June 1995 [doi>10.1006/jcss.1995.1045]
	7	Robert Daley, Bala Kalyan, and Mahe Velauthapillai. The power of probabilism in popperian finite learning. Journal of Experimental and Theoretical Atrijcial Intelligence, 6( 1):41-62, 1994.
	8	Robert P. Daley , Bala Kalyanasundaram, Towards Reduction Argumentf for FINite Learning, Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report, p.63-75, January 1995