881 search results - page 3 / 177 » Spectral Algorithms for Supervised Learning |
SDM
2007
SIAM
13 years 7 months ago
2007
SIAM
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
KDD
2008
ACM
14 years 6 months ago
2008
ACM
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
TIT
2008
13 years 5 months ago
2008
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
DAGM
2004
Springer
13 years 11 months ago
2004
Springer
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
AAAI
2010
13 years 7 months ago
2010
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...