On Bayes methods for on-line Boolean prediction

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On Bayes methods for on-line Boolean prediction

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

Desenzano del Garda, Italy

Pages: 314 - 324

Year of Publication: 1996

ISBN:0-89791-811-8

Authors

Nicolò Cesa-Bianchi	DSI, University of Milan, Italy
David P. Helmbold	University of California, Santa Cruz
Sandra Panizza	DSI, University of Milan, Italy

Sponsors

Univ degli Studi de Milano : Universite degli Studi de Milano
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): 22, Citation Count: 3

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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	Nicolo Cesa-Bianchi , Yoav Freund , David Helmbold , David Haussler , Robert Schapire , Manfred Warmuth, HOW TO USE EXPERT ADVICE, University of California at Santa Cruz, Santa Cruz, CA, 1995
	2	Nicolò Cesa-Bianchi , Yoav Freund , David P. Helmbold , Manfred K. Warmuth, On-line prediction and conversion strategies, Machine Learning, v.25 n.1, p.71-110, Oct. 1996 [doi>10.1023/A:1018348209754]
	3	A. Dawid. Statistical theory: the prequential approach. J. Roy. Statist. Soc. A, pages 278-292, 1984.
	4	M. Feder, N. Merhav, and M. Gutman. Universal prediction of individual sequences. IEEE Trans. on Information Theory, 38:1258-1270, 1992.
	5	D. Haussler and A. Barron. How well does the Bayes method work in on-line predictions of {+1,-1} values? In Proceedings of 3rd NEC Symposium, pages 74-100. SIAM, 1993.
	6	Jyrki Kivinen , Manfred K. Warmuth, Using experts for predicting continuous outcomes, Proceedings of the first European conference on Computational learning theory, p.109-120, October 1994, Royal Holloway, Univ. of London, United Kingdom
	7	N. Littlestone, Mistake bounds and logarithmic linear-threshold learning algorithms, University of California at Santa Cruz, Santa Cruz, CA, 1990
	8	Nick Littlestone , Manfred K. Warmuth, The weighted majority algorithm, Information and Computation, v.108 n.2, p.212-261, Feb. 1, 1994 [doi>10.1006/inco.1994.1009]
	9	V.G.Vovk. Prequential probability theory. Unpublished manuscript, 1990.
	10	Volodimir G. Vovk, Aggregating strategies, Proceedings of the third annual workshop on Computational learning theory, p.371-386, August 06-08, 1990, Rochester, New York, United States
	11	V. Vovk, A game of prediction with expert advice, Journal of Computer and System Sciences, v.56 n.2, p.153-173, April 1998 [doi>10.1006/jcss.1997.1556]

CITED BY 3

	Adam J. Grove , Nick Littlestone , Dale Schuurmans, General Convergence Results for Linear Discriminant Updates, Machine Learning, v.43 n.3, p.173-210, June 2001
	V. Vovk, Derandomizing Stochastic Prediction Strategies, Machine Learning, v.35 n.3, p.247-282, June 1999
	Adam J. Grove , Nick Littlestone , Dale Schuurmans, General convergence results for linear discriminant updates, Proceedings of the tenth annual conference on Computational learning theory, p.171-183, July 06-09, 1997, Nashville, Tennessee, United States