On prediction of individual sequences relative to a set of experts in the presence of noise

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On prediction of individual sequences relative to a set of experts in the presence of noise

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

Santa Cruz, California, United States

Pages: 19 - 28

Year of Publication: 1999

ISBN:1-58113-167-4

Authors

Tsachy Weissman	Department of Electrical Engineering, Technion, Haifa 32000, Israel
Neri Merhav	Department of Electrical Engineering, Technion, Haifa 32000, Israel

Sponsors

SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Univ. of California, : University of California at Santa Cruz

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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	Nicolò Cesa-Bianchi , Gábor Lugosi, On sequential prediction of individual sequences relative to a set of experts, Proceedings of the eleventh annual conference on Computational learning theory, p.1-11, July 24-26, 1998, Madison, Wisconsin, United States [doi>10.1145/279943.279946]
	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	M. Feder, N. Merhav, and M. Gutman, "Universal Prediction of Individual Sequences," IEEE Trans. Inform. Theory, vol. 38, pp. 1258-1270, July 1992.
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	5	N. Merhav, "Universal Coding with Minimum Probability of Codeword Length Overfiow,"IEEE Trans. Inform. Theory, vol. 37, pp. 556-563, May 1991.
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	7	D. Haussler, J. Kivinen, and M.K. Warmuth, "Sequential Prediction of Individual Sequences Under General Loss Functions", IEEE Trans. Inform. Theory, vol. 44, pp. 1906-1925, September 1998.
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	10	A. Dembo and O. Zeitouni, Large Deviations Techniques and Applications 2nd ed. Springer-Verlag, New York, 1998.
	11	W. Hoeffding, "Probability Inequalities for Sums of Bounded Random Variables", Journal of the American Statistical Association, 58:13-30, 1963.
	12	P. Hall and C.C. Heyde, Martingale Limit Theory and its Application Academic Press, New York, 1980.
	13	W.F. Stout, "A Martingale Analogue of Kolmogorov's Law of the Iterated Logarithm", Z. Wahrsch. Verw. Gebiete 15, 279-290.
	14	W.F. Stout, "The Hartman-Wintner Law of the Iterated Logarithm for Martingales", Ann. Math. Statist. 41, 2158-2160.
	15	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