543 search results - page 53 / 109 » A PAC-Style Model for Learning from Labeled and Unlabeled Da... |
TCS
2011
13 years 2 months ago
2011
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
COLING
2008
13 years 9 months ago
2008
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
NIPS
2007
13 years 9 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...
ISWC
2006
IEEE
14 years 2 months ago
2006
IEEE
Activity Recognition has gained a lot of interest in recent years due to its potential and usefulness for context-aware wearable computing. However, most approaches for activity r...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...