58 search results - page 7 / 12 » Approximation accuracy, gradient methods, and error bound fo... |
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
We propose a new semi-supervised model selection method that is derived by applying the structural risk minimization principle to a recent semi-supervised generalization error bou...
ICCV
2009
IEEE
15 years 22 days ago
2009
IEEE
The concept of graph cuts is by now a standard method
for all sorts of low level vision problems. Its popularity is
largely due to the fact that globally or near globally optimal...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
NIPS
2008
13 years 9 months ago
2008
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all di...
CORR
2012
Springer
12 years 3 months ago
2012
Springer
Graphs and networks are used to model interactions in a variety of contexts, and there is a growing need to be able to quickly assess the qualities of a graph in order to understa...