63 search results - page 9 / 13 » Complexity Bounds for Batch Active Learning in Classificatio... |
NIPS
2004
13 years 9 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...
ML
2002
ACM
13 years 7 months ago
2002
ACM
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
NIPS
2001
13 years 9 months ago
2001
We give results about the learnability and required complexity of logical formulae to solve classification problems. These results are obtained by linking propositional logic with...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...