Teachers, learners and black boxes

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Teachers, learners and black boxes

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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: 285 - 297

Year of Publication: 1997

ISBN:0-89791-891-6

Authors

Dana Angluin	Computer Science Department, Yale University, P.O. Box 208285, New Haven, CT
Mārtiņš Kriķis	Computer Science Department, Yale University, P.O. Box 208285, New Haven, CT

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

Bibliometrics

Downloads (6 Weeks): 4, Downloads (12 Months): 28, Citation Count: 2

Additional Information:

references cited by index terms collaborative colleagues

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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	L. Blum and M. Blum. Toward a mathematical theory of inductive inference. Itzfbrm. Control, 28(2): I25- 155, June 1975.
	2	Sally A. Goldman , H. David Mathias, Teaching a smarter learner, Journal of Computer and System Sciences, v.52 n.2, p.255-267, April 1996 [doi>10.1006/jcss.1996.0020]
	3	Sally A. Goldman , H. David Mathias, Teaching a smart learner, Proceedings of the sixth annual conference on Computational learning theory, p.67-76, July 26-28, 1993, Santa Cruz, California, United States [doi>10.1145/168304.168313]
	4	Jeffrey Jackson , Andrew Tomkins, A computational model of teaching, Proceedings of the fifth annual workshop on Computational learning theory, p.319-326, July 27-29, 1992, Pittsburgh, Pennsylvania, United States [doi>10.1145/130385.130421]
	5	Michael Machtey , Paul Young, An Introduction to the General Theory of Algorithms, Elsevier Science Inc., New York, NY, 1978
	6	H. David Mathias, DNF—if you can't learn'em, teach'em: an interactive model of teaching, Proceedings of the eighth annual conference on Computational learning theory, p.222-229, July 05-08, 1995, Santa Cruz, California, United States [doi>10.1145/225298.225325]
	7	E. Minicozzi. Some natural properties of strong identification in inductive inference. Thewet. Conzput. Sri.. 2345-360, 1976.
	8	Ayumi Shinohara , Satoru Miyano, Teachability in computational learning, New Generation Computing, v.8 n.4, p.337-347, 1991 [doi>10.1007/BF03037091]

CITED BY 2

	Stephen S. Kwek, An apprentice learning model (extended abstract), Proceedings of the twelfth annual conference on Computational learning theory, p.63-74, July 07-09, 1999, Santa Cruz, California, United States
	Frank J. Balbach, Measuring teachability using variants of the teaching dimension, Theoretical Computer Science, v.397 n.1-3, p.94-113, May, 2008