110 search results - page 11 / 22 » Boosting a Weak Learning Algorithm by Majority |
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
CVPR
2005
IEEE
14 years 1 months ago
2005
IEEE
With the aim to design a general learning framework for detecting faces of various poses or under different lighting conditions, we are motivated to formulate the task as a classi...
ECML
2007
Springer
14 years 1 months ago
2007
Springer
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...