BMCBI
2008
13 years 11 months ago
2008
Background: In metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the cu...
SDM
2007
SIAM
14 years 8 days ago
2007
SIAM
The recent years have witnessed a surge of interest in graphbased semi-supervised learning methods. The common denominator of these methods is that the data are represented by the...
IJCAI
2007
14 years 8 days ago
2007
This paper proposes and develops a new graph-based semi-supervised learning method. Different from previous graph-based methods that are based on discriminative models, our method...
ASUNAM
2010
IEEE
14 years 12 days 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...
AAAI
2008
14 years 1 months ago
2008
The recent years have witnessed a surge of interests in semi-supervised learning methods. A common strategy for these algorithms is to require that the predicted data labels shoul...
CICLING
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. We propose to use semi-supervised learning methods to classify evaluative expressions, that is, tuples of subjects, their attributes, and evaluative words, that indicate ...
ICPR
2008
IEEE
14 years 5 months ago
2008
IEEE
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
PKDD
2009
Springer
14 years 5 months ago
2009
Springer
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...