DOI: 10.1007/3-540-59119-2_166. A desicion-theoretic generalization of on-line learning and an application to boosting

A desicion-theoretic generalization of on-line learning and an application to boosting

10.1007/3-540-59119-2_166

Crossref book-chapter

Springer Berlin Heidelberg

Lecture Notes in Computer Science (297)

Bibliography

Freund, Y., & Schapire, R. E. (1995). A desicion-theoretic generalization of on-line learning and an application to boosting. Computational Learning Theory, 23â37.

Authors 2

Yoav Freund (first)
Robert E. Schapire (additional)

References 12 Referenced 1,907

Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, David Haussler, Robert E. Schapire, and Manfred K. Warmuth. How to use expert advice. In Proceedings of the Twenty-Fifth Annual ACM Symposium on the Theory of Computing, pages 382–391, May 1993. (10.1145/167088.167198)
Thomas H. Chung. Approximate methods for sequential decision making using expert advice. In Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, pages 183–189, 1994. (10.1145/180139.181097)
Thomas M. Cover. Universal portfolios. Mathematics of Finance, 1(1):1–29, January 1991. (10.1111/j.1467-9965.1991.tb00002.x) / Mathematics of Finance by M. Thomas (1991)
Harris Drucker, Robert Schapire, and Patrice Simard. Boosting performance in neural networks. International Journal of Pattern Recognition and Artificial Intelligence, 7(4):705–719, 1993. (10.1142/S0218001493000352) / International Journal of Pattern Recognition and Artificial Intelligence by H. Drucker (1993)
Yoav Freund. Data Filtering and Distribution Modeling Algorithms for Machine Learning. PhD thesis, University of California at Santa Cruz, 1993. Retrievable from: ftp.cse.ucsc.edu/pub/tr/ucsc-crl-93-37.ps.Z. / PhD thesis by Y. Freund (1993)
Yoav Freund. Boosting a weak learning algorithm by majority. Information and Computation, To appear.
James Hannan. Approximation to Bayes risk in repeated play. In M. Dresher, A. W. Tucker, and P. Wolfe, editors, Contributions to the Theory of Games, volume III, pages 97–139. Princeton University Press, 1957. (10.1515/9781400882151-006)
David Haussler, Jyrki Kivinen, and Manfred K. Warmuth. Tight worst-case loss bounds for predicting with expert advice. In Proceedings of the Second European Conference on Computational Learning Theory, 1995. (10.1007/3-540-59119-2_169)
Jyrki Kivinen and Manfred K. Warmuth. Using experts for predicting continuous outcomes. In Computational Learning Theory: EuroCOLT'93, pages 109–120, 1994.
Nick Littlestone and Manfred K. Warmuth. The weighted majority algorithm. Information and Computation, 108:212–261, 1994. (10.1006/inco.1994.1009) / Information and Computation by N. Littlestone (1994)
Robert E. Schapire. The strength of weak learnability. Machine Learning, 5(2):197–227, 1990. / Machine Learning by R. E. Schapire (1990)
Volodimir G. Vovk. Aggregating strategies. In Proceedings of the Third Annual Workshop on Computational Learning Theory, pages 371–383, 1990. (10.1016/B978-1-55860-146-8.50032-1)

Dates

Type	When
Created	13 years, 6 months ago (Feb. 26, 2012, 12:02 p.m.)
Deposited	4 years, 9 months ago (Nov. 17, 2020, 4:25 p.m.)
Indexed	1 day, 10 hours ago (Aug. 31, 2025, 7:32 p.m.)
Issued	30 years, 8 months ago (Jan. 1, 1995)
Published	30 years, 8 months ago (Jan. 1, 1995)
Published Online	20 years, 3 months ago (June 1, 2005)
Published Print	30 years, 8 months ago (Jan. 1, 1995)

Funders 0

None

BibTeX

@inbook{Freund_1995, title={A desicion-theoretic generalization of on-line learning and an application to boosting}, ISBN={9783540491958}, ISSN={1611-3349}, url={http://dx.doi.org/10.1007/3-540-59119-2_166}, DOI={10.1007/3-540-59119-2_166}, booktitle={Computational Learning Theory}, publisher={Springer Berlin Heidelberg}, author={Freund, Yoav and Schapire, Robert E.}, year={1995}, pages={23–37} }

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