571 search results - page 11 / 115 » Learning with Constrained and Unlabelled Data |
KDD
2002
ACM
14 years 10 months ago
2002
ACM
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
NIPS
2004
13 years 11 months ago
2004
In the context of binary classification, we define disagreement as a measure of how often two independently-trained models differ in their classification of unlabeled data. We exp...
IJCAI
2007
13 years 11 months ago
2007
An “active learning system” will sequentially decide which unlabeled instance to label, with the goal of efficiently gathering the information necessary to produce a good cla...
COLING
2010
13 years 5 months ago
2010
We demonstrate the use of context features, namely, names of places, and unlabelled data for the detection of personal name language of origin. While some early work used either r...
SIGIR
2008
ACM
13 years 10 months ago
2008
ACM
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...