46 search results - page 1 / 10 » Manifold Regularization: A Geometric Framework for Learning ... |
JMLR
2006
13 years 4 months ago
2006
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
Labeling image collections is a tedious task, especially
when multiple labels have to be chosen for each image. In
this paper we introduce a new framework that extends state
of ...
ICPR
2008
IEEE
13 years 10 months ago
2008
IEEE
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regulari...
NIPS
2004
13 years 5 months ago
2004
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...