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» Learning from Skewed Class Multi-relational Databases
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CVPR
2012
IEEE
11 years 11 months ago
Large-scale knowledge transfer for object localization in ImageNet
ImageNet is a large-scale database of object classes with millions of images. Unfortunately only a small fraction of them is manually annotated with bounding-boxes. This prevents ...
Matthieu Guillaumin, Vittorio Ferrari
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
13 years 10 months ago
Roughly Balanced Bagging for Imbalanced Data
Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...
Shohei Hido, Hisashi Kashima
CVPR
2012
IEEE
11 years 11 months ago
Meta-class features for large-scale object categorization on a budget
In this paper we introduce a novel image descriptor enabling accurate object categorization even with linear models. Akin to the popular attribute descriptors, our feature vector ...
Alessandro Bergamo, Lorenzo Torresani
CVPR
2010
IEEE
14 years 1 months ago
Adaptive Generic Learning for Face Recognition from a Single Sample per Person
Real-world face recognition systems often have to face the single sample per person (SSPP) problem, that is, only a single training sample for each person is enrolled in the datab...
Yu Su, Shiguang Shan, Xilin Chen, wen Gao
ICDM
2009
IEEE
200views Data Mining» more  ICDM 2009»
13 years 6 months ago
Improving SVM Classification on Imbalanced Data Sets in Distance Spaces
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...
Suzan Koknar-Tezel, Longin Jan Latecki