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ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
14 years 2 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
IJDAR
2008
121views more  IJDAR 2008»
13 years 7 months ago
Partial discriminative training for classification of overlapping classes in document analysis
For character recognition in document analysis, some classes are closely overlapped but are not necessarily to be separated before contextual information is exploited. For classifi...
Cheng-Lin Liu
VISUAL
2005
Springer
14 years 27 days ago
Face Recognition Using Modular Bilinear Discriminant Analysis
We present a Modular Bilinear Disciminant Analysis (MBDA) approach for face recognition. A set of classifiers are trained independently on specific face regions, and different c...
Muriel Visani, Christophe Garcia, Jean-Michel Joli...
ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
13 years 11 months ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
Qi Tian, Ying Wu, Thomas S. Huang
AAAI
2010
13 years 7 months ago
Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories
Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...
Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bi...