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CEAS
2007
Springer
14 years 25 days ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
ICML
2009
IEEE
14 years 9 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
AIRS
2008
Springer
14 years 3 months ago
Active Learning for Online Spam Filtering
Spam filtering is defined as a task trying to label emails with spam or ham in an online situation. The online feature requires the spam filter has a strong timely generalization a...
Wuying Liu, Ting Wang
EUROCOLT
1995
Springer
14 years 12 days ago
A decision-theoretic generalization of on-line learning and an application to boosting
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
Yoav Freund, Robert E. Schapire
ETS
2002
IEEE
99views Hardware» more  ETS 2002»
13 years 8 months ago
Online Learning Technology in an SME Work-Based Setting
Over the last 20 years there has been increasing interest in work-based learning in the UK business sector as a means to improve and increase the skills of the UK workforce. The m...
Bernd Brink, John Munro, Mike Osborne