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» Geometric Bounds for Generalization in Boosting
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COMPGEOM
1993
ACM
13 years 9 months ago
Worst-Case Bounds for Subadditive Geometric Graphs
We consider graphs such as the minimum spanning tree, minimum Steiner tree, minimum matching, and traveling salesman tour for n points in the d-dimensional unit cube. For each of ...
Marshall W. Bern, David Eppstein
ICML
2009
IEEE
14 years 6 months ago
PAC-Bayesian learning of linear classifiers
We present a general PAC-Bayes theorem from which all known PAC-Bayes risk bounds are obtained as particular cases. We also propose different learning algorithms for finding linea...
Alexandre Lacasse, François Laviolette, Mar...
TIT
2002
164views more  TIT 2002»
13 years 5 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini
ML
2002
ACM
145views Machine Learning» more  ML 2002»
13 years 5 months ago
Boosting Methods for Regression
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Nigel Duffy, David P. Helmbold
COLT
2008
Springer
13 years 7 months ago
On the Margin Explanation of Boosting Algorithms
Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bou...
Liwei Wang, Masashi Sugiyama, Cheng Yang, Zhi-Hua ...