45 search results - page 6 / 9 » Boosting in the Limit: Maximizing the Margin of Learned Ense... |
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
3DPVT
2004
IEEE
13 years 11 months ago
2004
IEEE
This paper proposes the use of neural network ensembles to boost the performance of a neural network based surface reconstruction algorithm. Ensemble is a very popular and powerfu...
JMLR
2008
13 years 7 months ago
2008
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
PAMI
2012
11 years 10 months ago
2012
—It has been shown that the Universum data, which do not belong to either class of the classification problem of interest, may contain useful prior domain knowledge for training...
NIPS
2004
13 years 9 months ago
2004
We establish a mistake bound for an ensemble method for classification based on maximizing the entropy of voting weights subject to margin constraints. The bound is the same as a ...