571 search results - page 48 / 115 » Learning with Constrained and Unlabelled Data |
NIPS
2007
13 years 11 months ago
2007
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
IJCNN
2006
IEEE
14 years 4 months ago
2006
IEEE
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
TCS
2011
13 years 4 months ago
2011
An active learner has a collection of data points, each with a label that is initially hidden but can be obtained at some cost. Without spending too much, it wishes to find a cla...
NIPS
1992
13 years 11 months ago
1992
Vector Quantization is useful for data compression. Competitive Learning which minimizes reconstruction error is an appropriate algorithm for vector quantization of unlabelled dat...