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CEAS
2007
Springer
13 years 11 months 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
AVSS
2006
IEEE
14 years 1 months ago
An Online Discriminative Approach to Background Subtraction
We present a simple, principled approach to detecting foreground objects in video sequences in real-time. Our method is based on an on-line discriminative learning technique that ...
Li Cheng, Shaojun Wang, Dale Schuurmans, Terry Cae...
ICML
2009
IEEE
14 years 8 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 2 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
13 years 11 months 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