Muller KR, Ratsch G, Onoda T. (2001). Soft margins for AdaBoost Mach Learn. 42

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

Andelić E, Schafföner M, Katz M, Krüger SE, Wendemuth A. (2006). Kernel least-squares models using updates of the pseudoinverse. Neural computation. 18 [PubMed]

Blanchard G. (2004). Different Paradigms for Choosing Sequential Reweighting Algorithms Neural Comput. 16

Hochreiter S, Obermayer K. (2006). Support vector machines for dyadic data. Neural computation. 18 [PubMed]

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

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

Washizawa Y, Yamashita Y. (2006). Kernel projection classifiers with suppressing features of other classes. Neural Comput. 18

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