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ICDM
2003
IEEE
143views Data Mining» more  ICDM 2003»
14 years 1 months ago
Active Sampling for Feature Selection
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
Sriharsha Veeramachaneni, Paolo Avesani
CVPR
2007
IEEE
14 years 9 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
MLDM
2007
Springer
14 years 1 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...
CEAS
2004
Springer
14 years 1 months ago
The Impact of Feature Selection on Signature-Driven Spam Detection
Signature-driven spam detection provides an alternative to machine learning approaches and can be very effective when near-duplicates of essentially the same message are sent in h...
Aleksander Kolcz, Abdur Chowdhury, Joshua Alspecto...
ICMCS
2009
IEEE
215views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Image trimming via saliency region detection and iterative feature matching
Detection of saliency regions in images is useful for object based image understanding and object localization. In our work, we investigate a saliency region detection algorithm b...
Jiawei Huang, Ze-Nian Li