The Strength of Weak Learnability
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Cites methods from "The Strength of Weak Learnability"
...Compare earlier, more sophisticated ensemble methods (Schapire, 1990), the contest-winning ensemble Bayes-NN (Neal, 2006) of Section 5.14, and recent related work (Shao, Wu, & Li, 2014)....
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...Multi-Column GPU-MPCNNs (Ciresan, Meier, Masci, & Schmidhuber, 2011) are committees (Breiman, 1996; Dietterich, 2000a; Hashem & Schmeiser, 1992; Schapire, 1990; Ueda, 2000; Wolpert, 1992) of GPU-MPCNNs with simple democratic output averaging....
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...A Bayes NN (Neal, 2006) based on an ensemble (Breiman, 1996; Dietterich, 2000a; Hashem & Schmeiser, 1992; Schapire, 1990; Ueda, 2000; Wolpert, 1992) of NNs won the NIPS 2003 Feature Selection Challenge with secret test set (Neal & Zhang, 2006)....
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...ensemble methods (Schapire, 1990), the contest-winning ensem-...
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Cites background from "The Strength of Weak Learnability"
...Boosting was originally derived in the computational learning theory literature (Schapire 1990; Freund and Schapire 1996), where the focus is binary classification....
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References
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"The Strength of Weak Learnability" refers background in this paper
...Thus, f(0) = e > 3e/4, and, using our bound for e and the fact that e = 3a 2 -2a 3 , To bound the number of examples needed to estimate a 1 and e, we will make use of the following bounds on the tails of a binomial distribution (Angluin and Valiant, 1979; Hoeffding, 1963)....
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