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» Robust classification for skewed data
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ICASSP
2010
IEEE
13 years 7 months ago
Hierarchical dictionary learning for invariant classification
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
Leah Bar, Guillermo Sapiro
BMCBI
2007
154views more  BMCBI 2007»
13 years 7 months ago
Classification of heterogeneous microarray data by maximum entropy kernel
Background: There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are c...
Wataru Fujibuchi, Tsuyoshi Kato
BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
CVPR
2008
IEEE
14 years 9 months ago
On the use of independent tasks for face recognition
We present a method for learning discriminative linear feature extraction using independent tasks. More concretely, given a target classification task, we consider a complementary...
Àgata Lapedriza, David Masip, Jordi Vitri&a...
ICCD
1995
IEEE
51views Hardware» more  ICCD 1995»
13 years 11 months ago
Implementing a STARI chip
STARI is a high-speed signaling technique that uses both synchronous and self-timed circuits. To demonstrate STARI, a chip has been fabricated using the MOSIS 2 CMOS process. In a...
Mark R. Greenstreet