40 search results - page 3 / 8 » Learning Permutations with Exponential Weights |
ICPR
2000
IEEE
14 years 8 months ago
2000
IEEE
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
We propose preprocessing spectral clustering with b-matching to remove spurious edges in the adjacency graph prior to clustering. B-matching is a generalization of traditional maxi...
ICANN
2003
Springer
14 years 22 days ago
2003
Springer
Pattern recognition problems span a broad range of applications, where each application has its own tolerance on classification error. The varying levels of risk associated with ma...
COLT
2005
Springer
14 years 1 months ago
2005
Springer
We discuss a simple sparse linear problem that is hard to learn with any algorithm that uses a linear combination of the training instances as its weight vector. The hardness holds...
EUROCOLT
1999
Springer
13 years 11 months ago
1999
Springer
We consider algorithms for combining advice from a set of experts. In each trial, the algorithm receives the predictions of the experts and produces its own prediction. A loss func...