70 search results - page 5 / 14 » Boosting Based on a Smooth Margin |
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
The application of semi-supervised learning algorithms to large scale vision problems suffers from the bad scaling behavior of most methods. Based on the Expectation Regularization...
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...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
A multiclass classification problem can be reduced to a collection of binary problems with the aid of a coding matrix. The quality of the final solution, which is an ensemble of b...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
Feature selection plays a fundamental role in many pattern
recognition problems. However, most efforts have been
focused on the supervised scenario, while unsupervised feature
s...
IJCAI
2007
13 years 9 months ago
2007
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...