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COLING
2010
15 years 26 days ago
A Comparison of Models for Cost-Sensitive Active Learning
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Katrin Tomanek, Udo Hahn
CVPR
2008
IEEE
16 years 7 months ago
Learning patch correspondences for improved viewpoint invariant face recognition
Variation due to viewpoint is one of the key challenges that stand in the way of a complete solution to the face recognition problem. It is easy to note that local regions of the ...
Ahmed Bilal Ashraf, Simon Lucey, Tsuhan Chen
ECCV
2008
Springer
16 years 7 months ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert
ICDM
2009
IEEE
111views Data Mining» more  ICDM 2009»
16 years 16 days ago
A Game Theoretical Model for Adversarial Learning
Abstract—It is now widely accepted that in many situations where classifiers are deployed, adversaries deliberately manipulate data in order to reduce the classifier’s accura...
Wei Liu, Sanjay Chawla
EPIA
2009
Springer
16 years 13 days ago
Learning Visual Object Categories with Global Descriptors and Local Features
Different types of visual object categories can be found in real-world applications. Some categories are very heterogeneous in terms of local features (broad categories) while oth...
Rui Pereira, Luís Seabra Lopes