Teaching a smart learner

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Teaching a smart learner

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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: 67 - 76

Year of Publication: 1993

ISBN:0-89791-611-5

Authors

Sally A. Goldman
H. David Mathias

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

Bibliometrics

Downloads (6 Weeks): 14, Downloads (12 Months): 29, Citation Count: 8

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	Howard Aizenstein, Lisa Itellerstein, and Leonard Pitt. Read-thrice DNF is hard to learn with membership and equivalence queries. In 33nd Annual Symposium on Foundations of Computer Science, pages 523-532, October 1992.
	2	Dana Angluin, Queries and Concept Learning, Machine Learning, v.2 n.4, p.319-342, April 1988 [doi>10.1023/A:1022821128753]
	3	Dana Angluin, Michael Fra~ier, and Leonard Pitt. Learning conjunctions of horn clauses. In 31st Annual Symposium on Foundations of Computer Science, pages 186-192, October 1990.
	4	Dana Angluin , Michael Frazier , Leonard Pitt, Learning Conjunctions of Horn Clauses, Machine Learning, v.9 n.2-3, p.147-164, July 1992 [doi>10.1007/BF00992675]
	5	Martin Anthony , Graham Brightwell , Dave Cohen , John Shawe-Taylor, On exact specification by examples, Proceedings of the fifth annual workshop on Computational learning theory, p.311-318, July 27-29, 1992, Pittsburgh, Pennsylvania, United States [doi>10.1145/130385.130420]
	6	J. Barzdin and R. Freivald. On the prediction of general recursive functions. Soviet Mathematics Doklady, 13:1224-1228, 1972.
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	8	R. Freivalds , E. B. Kinber , R. Wiehagen, On the power of inductive inference from good examples, Theoretical Computer Science, v.110 n.1, p.131-144, March 15, 1993 [doi>10.1016/0304-3975(93)90353-U]
	9	Sally A. Goldman , Michael J. Kearns, On the complexity of teaching, Proceedings of the fourth annual workshop on Computational learning theory, p.303-314, August 05-07, 1991, Santa Cruz, California, United States
	10	Sally A. Goldman , Ronald L. Rivest , Robert E. Schapire, Learning binary relations and total orders, SIAM Journal on Computing, v.22 n.5, p.1006-1034, Oct. 1993 [doi>10.1137/0222062]
	11	Sally A. Goldman and Robert H. Slosh. The power of self-directed learning. Technical Report WUCS-92--49, Washington University, Department of Computer Science, November 1992. To appear in Machine Learning.
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	13	Thomas R. Hancock, Identifying μ-formula decision trees with queries, Proceedings of the third annual workshop on Computational learning theory, p.23-37, August 06-08, 1990, Rochester, New York, United States
	14	David Helmbold , Robert Sloan , Manfred K. Warmuth, Learning Nested Differences of Intersection-Closed Concept Classes, Machine Learning, v.5 n.2, p.165-196, Jun. 1990 [doi>10.1023/A:1022696716689]
	15	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]
	16	Steffen Lange , Rolf Wiehagen, Polynomial-time inference of arbitrary pattern languages, New Generation Computing, v.8 n.4, p.361-370, 1991 [doi>10.1007/BF03037093]
	17	Nick Littlestone, Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm, Machine Learning, v.2 n.4, p.285-318, April 1988 [doi>10.1023/A:1022869011914]
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	19	Thomas M. Mitchell. Version spaces: A candidate elimination approach to rule learning. In Proceedings IJCAI- 77, pages 305-310. International Joint Committee for Artificial Intelligence, August 1977.
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	23	Kathleen Romanik , Carl Smith, Testing geometric objects, University of Maryland at College Park, College Park, MD, 1990
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	27	E. Welzl. Complete range spaces. Unpublished manuscript, 1987.

CITED BY 8

	Rajesh Parekh , Vasant G. Honavar, Learning DFA from Simple Examples, Machine Learning, v.44 n.1-2, p.9-35, July-August 2001
	Dana Angluin , Mārtiņš Kriķis, Teachers, learners and black boxes, Proceedings of the tenth annual conference on Computational learning theory, p.285-297, July 06-09, 1997, Nashville, Tennessee, United States
	Ronald L. Rivest , Yiqun Lisa Yin, Being taught can be faster than asking questions, Proceedings of the eighth annual conference on Computational learning theory, p.144-151, July 05-08, 1995, Santa Cruz, California, United States
	Yiqun Lisa Yin, Reducing the number of queries in self-directed learning, Proceedings of the eighth annual conference on Computational learning theory, p.128-135, July 05-08, 1995, Santa Cruz, California, United States
	Tibor Hegedűs, Geometrical concept learning and convex polytopes, Proceedings of the seventh annual conference on Computational learning theory, p.228-236, July 12-15, 1994, New Brunswick, New Jersey, United States
	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
	Steffen Lange , Jochen Nessel , Rolf Wiehagen, Learning recursive languages from good examples, Annals of Mathematics and Artificial Intelligence, v.23 n.1-2, p.27-52, 1998
	Reza Ebrahimpour , Ehsanollah Kabir , Mohammad Reza Yousefi, Teacher-directed learning in view-independent face recognition with mixture of experts using overlapping eigenspaces, Computer Vision and Image Understanding, v.111 n.2, p.195-206, August, 2008