358 search results - page 30 / 72 » Learning from labeled and unlabeled data on a directed graph |
ICML
2006
IEEE
16 years 18 days ago
2006
IEEE
Many real-world sequence learning tasks require the prediction of sequences of labels from noisy, unsegmented input data. In speech recognition, for example, an acoustic signal is...
NIPS
2007
15 years 1 months ago
2007
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
110
click to vote
ICML
2005
IEEE
16 years 18 days ago
2005
IEEE
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
MVA
2007
15 years 1 months ago
2007
For a social robot, the ability of learning tasks via human demonstration is very crucial. But most current approaches suffer from either the demanding of the huge amount of label...
103
click to vote
WAIM
2009
Springer
15 years 4 months ago
2009
Springer
In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...