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152
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JMLR
2006
105views more  JMLR 2006»
15 years 6 months ago
Some Theory for Generalized Boosting Algorithms
We give a review of various aspects of boosting, clarifying the issues through a few simple results, and relate our work and that of others to the minimax paradigm of statistics. ...
Peter J. Bickel, Yaacov Ritov, Alon Zakai
153
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ALT
2004
Springer
16 years 3 months ago
Learning r-of-k Functions by Boosting
We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
Kohei Hatano, Osamu Watanabe
141
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ISCAS
1999
IEEE
122views Hardware» more  ISCAS 1999»
15 years 10 months ago
Convergence properties of mixed-norm algorithms under general error criteria
Tareq Y. Al-Naffouri, Azzedine Zerguine, M. Bettay...
166
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CORR
2011
Springer
127views Education» more  CORR 2011»
14 years 10 months ago
Generalized Boosting Algorithms for Convex Optimization
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
Alexander Grubb, J. Andrew Bagnell