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Boosting combines weak classifiers to form highly accurate predictors.
Convex Analysis
R. Tyrrell Rockafellar · 1970
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The strength of weak learnability
Robert E. Schapire · 1990
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Solving multiclass learning problems via error-correcting output codes
Thomas G. Dietterich and Ghulum Bakiri · 1995
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Boosting a weak learning algorithm by majority
Yoav Freund · 1995
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A decision-theoretic generalization of on-line learning and an application to boosting
Yoav Freund and Robert E. Schapire · 1997
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Classification by pairwise coupling
Trevor Hastie and Robert Tibshirani · 1998
Earlier work this paper cites.
Boosting the margin: A new explanation for the effectiveness of voting methods
Robert E. Schapire, Yoav Freund, Peter Bartlett, and Wee Sun Lee · 1998
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Improved boosting algorithms using confidence-rated predictions
Robert E. Schapire and Yoram Singer · 1999
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Reducing multiclass to binary: A unifying approach for margin classifiers
Erin L. Allwein, Robert E. Schapire, and Yoram Singer · 2000
Earlier work this paper cites.
BoosTexter: A boosting-based system for text categorization
Robert E. Schapire and Yoram Singer · 2000
Cited alongside, same era.
An adaptive version of the boost by majority algorithm
Yoav Freund · 2001
Cited alongside, same era.
Drifting games
Robert E. Schapire · 2001
Cited alongside, same era.
Continuous drifting games
Yoav Freund and Manfred Opper · 2002
Cited alongside, same era.
Empirical margin distributions and bounding the generalization error of combined classifiers
V. Koltchinskii and D. Panchenko · 2002
Cited alongside, same era.
Statistical behavior and consistency of classification methods based on convex risk minimization
Tong Zhang · 2004
Cited alongside, same era.
AdaBoost is consistent
Peter L. Bartlett and Mikhail Traskin · 2007
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On the Consistency of Multiclass Classification Methods
Ambuj Tewari and Peter L. Bartlett · 2007
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Optimal stragies and minimax lower bounds for online convex games
Jacob Abernethy, Peter L. Bartlett, Alexander Rakhlin, and Ambuj Tewari · 2008
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Error-correcting tournaments
Alina Beygelzimer, John Langford, and Pradeep Ravikumar · 2009
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Multi-class AdaBoost
Ji Zhu, Hui Zou, Saharon Rosset, and Trevor Hastie · 2009
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Random classification noise defeats all convex potential boosters
Philip M. Long and Rocco A. Servedio · 2010
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Multiclass boosting for weak classifiers
Günther Eibl and Karl-Peter Pfeiffer · 2005
Cited alongside, same era.
Efficient margin maximizing with boosting
Gunnar Rätsch and Manfred K. Warmuth · 2005
Cited alongside, same era.
Convexity, classification, and risk bounds
Peter L. Bartlett, Michael I. Jordan, and Jon D. McAuliffe · 2006
Cited alongside, same era.
Experiments with a new boosting algorithm
Yoav Freund and Robert E. Schapire
Cited in the paper.
Game theory, on-line prediction and boosting
Yoav Freund and Robert E. Schapire
Cited in the paper.
Learning with continuous experts using drifting games
Indraneel Mukherjee and Robert E. Schapire · 2010
Later among the works it cites.
The rate of convergence of AdaBoost
Indraneel Mukherjee, Cynthia Rudin, and Robert E. Schapire · 2011
Closest in time.
Boosting: Foundations and Algorithms
Robert E. Schapire and Yoav Freund · 2012
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