393 search results - page 10 / 79 » On the Convergence of Boosting Procedures |
ICML
2004
IEEE
14 years 9 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...
MP
2002
13 years 8 months ago
2002
The efficient solution of large-scale linear and nonlinear optimization problems may require exploiting any special structure in them in an efficient manner. We describe and analy...
ICPR
2000
IEEE
14 years 29 days ago
2000
IEEE
In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
Several authors have suggested viewing boosting as a gradient descent search for a good fit in function space. At each iteration observations are re-weighted using the gradient of...
ICML
2004
IEEE
14 years 9 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. ...