On sequential prediction of individual sequences relative to a set of experts

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On sequential prediction of individual sequences relative to a set of experts

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

Madison, Wisconsin, United States

Pages: 1 - 11

Year of Publication: 1998

ISBN:1-58113-057-0

Authors

Nicolò Cesa-Bianchi	Department of Information Sciences, University of Milan, Via Comelico 39, 20135 Milano, Italy
Gábor Lugosi	Department of Economics, Pompeu Fabra University, Ramon Trias Fargas 25-27, 08005 Barcelona, Spain

Sponsors

University of Wisconsin : University of Wisconsin
UC @ Santa Cruz : UC @ Santa Cruz
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): 2, 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	K. Azuma. Weighted sums of certain dependent random variables. Tohoku Mathematical Journal, 68:357- 367, 1967.
	2	Nicolò Cesa-Bianchi , Yoav Freund , David Haussler , David P. Helmbold , Robert E. Schapire , Manfred K. Warmuth, How to use expert advice, Journal of the ACM (JACM), v.44 n.3, p.427-485, May 1997 [doi>10.1145/258128.258179]
	3	Nicolò Cesa-Bianchi, Analysis of two gradient-based algorithms for on-line regression, Proceedings of the tenth annual conference on Computational learning theory, p.163-170, July 06-09, 1997, Nashville, Tennessee, United States [doi>10.1145/267460.267492]
	4	Y.S. Chow and H. Teicher. Probability Theory, Independence, Interchangeability, Martingales. Springer- Verlag, New York, 1978.
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	7	L. Devroye, L. Gy6rfi, and G. Lugosi. A Probabilistic Theory of Pattern Recognition. Springer-Verlag, New York, 1996.
	8	M. Feder, N. Merhav, and M. Gutman. Universal prediction of individual sequences. IEEE Transactions on Information Theory, 38:1258-1270, 1992.
	9	E.N. Gilbert. A comparison of signalling alphabets. Bell System Technical Journal, 31:504-522, 1952.
	10	W. Hoeffding. Probability inequalities for sums of bounded random variables. Journal of the American Statistical Association, 58:13-30, 1963.
	11	M. Ledoux and M. Talagrand. Probability in Banach Space. Springer-Verlag, New York, 1991.
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	14	M. Opper and D. Haussler. Worst case prediction over sequences under log loss. In The Mathematics oflnformation Coding, Extraction and Distribution, Springer- Verlag, New York, 1998.
	15	D. Pollard. Asymptotics via empirical processes. Statistical Science, 4:341-366, 1989.
	16	S.J. Szarek. On the best constants in the Khintchine inequality. Studia Mathematica, 63:197-208, 1976.
	17	M. Talagrand. Majorizing measures: the generic chaining. Annals of Probability, 24:1049-1103, 1996. (Special Invited Paper).
	18	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