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» Learning from Skewed Class Multi-relational Databases
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CVPR
2012
IEEE
13 years 2 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»
15 years 1 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
13 years 2 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
15 years 5 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»
14 years 9 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