543 search results - page 27 / 109 » A PAC-Style Model for Learning from Labeled and Unlabeled Da... |
COLT
2003
Springer
14 years 1 months ago
2003
Springer
Abstract. We study the problem of learning partitions using equivalence constraints as input. This is a binary classification problem in the product space of pairs of datapoints. ...
ASUNAM
2010
IEEE
13 years 9 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...
ICDM
2006
IEEE
14 years 2 months ago
2006
IEEE
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
ADMA
2009
Springer
14 years 2 months ago
2009
Springer
Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a s...
ML
2010
ACM
13 years 6 months ago
2010
ACM
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...