7 search results - page 1 / 2 » Clustering-Based Feature Selection in Semi-supervised Proble... |
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
CIVR
2008
Springer
13 years 9 months ago
2008
Springer
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
ISDA
2009
IEEE
14 years 2 months ago
2009
IEEE
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
SBACPAD
2005
IEEE
14 years 1 months ago
2005
IEEE
The time required to simulate a complete benchmark program using the cycle-accurate model of a microprocessor can be prohibitively high. One of the proposed methodologies, represe...