221 search results - page 1 / 45 » Learning from Labeled and Unlabeled Data Using Random Walks |
DAGM
2004
Springer
13 years 10 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...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We consider the problem of multiclass classification where both labeled and unlabeled data points are given. We introduce and demonstrate a new approach for estimating a distribut...
NIPS
1998
1998
Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
13 years 6 months ago
This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
ASUNAM
2010
IEEE
13 years 6 months ago
2010
IEEE
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...