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» Classifier Selection Based on Data Complexity Measures
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BMCBI
2006
190views more  BMCBI 2006»
14 years 10 months ago
SNPs3D: Candidate gene and SNP selection for association studies
Background: The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and databas...
Peng Yue, Eugene Melamud, John Moult
102
Voted
PRL
2010
209views more  PRL 2010»
14 years 5 months ago
Efficient update of the covariance matrix inverse in iterated linear discriminant analysis
For fast classification under real-time constraints, as required in many imagebased pattern recognition applications, linear discriminant functions are a good choice. Linear discr...
Jan Salmen, Marc Schlipsing, Christian Igel
MICRO
2002
IEEE
164views Hardware» more  MICRO 2002»
15 years 3 months ago
A quantitative framework for automated pre-execution thread selection
Pre-execution attacks cache misses for which conventional address-prediction driven prefetching is ineffective. In pre-execution, copies of cache miss computations are isolated fr...
Amir Roth, Gurindar S. Sohi
CVPR
2006
IEEE
16 years 6 days ago
On-line Boosting and Vision
Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which impl...
Helmut Grabner, Horst Bischof
96
Voted
EUROGP
2004
Springer
133views Optimization» more  EUROGP 2004»
15 years 3 months ago
Lymphoma Cancer Classification Using Genetic Programming with SNR Features
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produc...
Jin-Hyuk Hong, Sung-Bae Cho