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ICML
2006
IEEE
14 years 8 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis
ML
2010
ACM
138views Machine Learning» more  ML 2010»
13 years 2 months ago
Mining adversarial patterns via regularized loss minimization
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
Wei Liu, Sanjay Chawla
CNIS
2006
13 years 8 months ago
Dynamically blocking access to web pages for spammers' harvesters
Almost all current anti spam measures are reactive, filtering being the most common. But to react means always to be one step behind. Reaction requires to predict the next action ...
Tobias Eggendorfer, Jörg Keller
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 7 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han