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» Random Sampling for Subspace Face Recognition
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MCS
2007
Springer
14 years 1 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
PAMI
2006
227views more  PAMI 2006»
13 years 7 months ago
Matching 2.5D Face Scans to 3D Models
The performance of face recognition systems that use two-dimensional images depends on factors such as lighting and subject's pose. We are developing a face recognition system...
Xiaoguang Lu, Anil K. Jain, Dirk Colbry
TCSV
2008
195views more  TCSV 2008»
13 years 7 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
PAKDD
2010
ACM
134views Data Mining» more  PAKDD 2010»
13 years 9 months ago
Generating Diverse Ensembles to Counter the Problem of Class Imbalance
Abstract. One of the more challenging problems faced by the data mining community is that of imbalanced datasets. In imbalanced datasets one class (sometimes severely) outnumbers t...
T. Ryan Hoens, Nitesh V. Chawla
PR
2008
161views more  PR 2008»
13 years 7 months ago
A study on three linear discriminant analysis based methods in small sample size problem
In this paper, we make a study on three Linear Discriminant Analysis (LDA) based methods: Regularized Discriminant Analysis (RDA), Discriminant Common Vectors (DCV) and Maximal Ma...
Jun Liu, Songcan Chen, Xiaoyang Tan