90 search results - page 2 / 18 » Semi-Supervised Learning with Very Few Labeled Training Exam... |
NIPS
2007
13 years 6 months ago
2007
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
NIPS
2003
13 years 6 months ago
2003
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
ACL
2007
13 years 6 months ago
2007
Over the last few years, two of the main research directions in machine learning of natural language processing have been the study of semi-supervised learning algorithms as a way...
ICASSP
2010
IEEE
13 years 5 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...
AAAI
2010
13 years 6 months ago
2010
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...