223 search results - page 7 / 45 » Spectral Learning |
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data poin...
ICDM
2007
IEEE
14 years 5 days ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
PAKDD
2004
ACM
14 years 1 months ago
2004
ACM
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
NIPS
2007
13 years 9 months ago
2007
Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...