159 search results - page 6 / 32 » Geometric Bounds for Generalization in Boosting |
ALT
2008
Springer
14 years 4 months ago
2008
Springer
In this paper we discuss boosting algorithms that maximize the soft margin of the produced linear combination of base hypotheses. LPBoost is the most straightforward boosting algor...
IDA
2002
Springer
13 years 7 months ago
2002
Springer
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifi...
COLT
2005
Springer
14 years 27 days ago
2005
Springer
We present a new generalization bound where the use of unlabeled examples results in a better ratio between training-set size and the resulting classifier’s quality and thus red...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
FOCS
2010
IEEE
13 years 5 months ago
2010
IEEE
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...