Freund Y, Schapire R. (1997). A decision-theoretic generalization of on-line learning and an application to boosting J Comput Sys Sci. 55

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References and models cited by this paper
References and models that cite this paper

Jiang W. (2004). Boosting with Noisy Data: Some Views from Statistical Theory Neural Comput. 16

Kanamori T, Takenouchi T, Eguchi S, Murata N. (2007). Robust loss functions for boosting. Neural computation. 19 [PubMed]

Murata N, Takenouchi T, Kanamori T, Eguchi S. (2004). Information geometry of U-Boost and Bregman divergence. Neural computation. 16 [PubMed]

Shrestha DL, Solomatine DP. (2006). Experiments with AdaBoost.RT, an improved boosting scheme for regression. Neural computation. 18 [PubMed]

Takenouchi T, Eguchi S. (2004). Robustifying AdaBoost by adding the naive error rate. Neural computation. 16 [PubMed]

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