90 search results - page 12 / 18 » Semi-Supervised Learning with Very Few Labeled Training Exam... |
CVPR
2010
IEEE
14 years 3 months ago
2010
IEEE
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
TKDE
2010
13 years 5 months ago
2010
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
DAGM
2008
Springer
13 years 9 months ago
2008
Springer
Three-dimensional electron-microscopic image stacks with almost isotropic resolution allow, for the first time, to determine the complete connection matrix of parts of the brain. I...
JMLR
2010
13 years 2 months ago
2010
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...