719 search results - page 42 / 144 » Discriminative learning for differing training and test dist... |
ACL
2009
14 years 7 months ago
2009
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
DMIN
2006
14 years 11 months ago
2006
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
EMNLP
2009
14 years 7 months ago
2009
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The res...
NAACL
1994
14 years 11 months ago
1994
We attemped to improve recognition accuracy by reducing the inadequacies of the lexicon and language model. Specifically we address the following three problems: (1) the best size...
CVPR
2006
IEEE
15 years 11 months ago
2006
IEEE
Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoret...