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» Entropy Numbers, Operators and Support Vector Kernels
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CIBCB
2007
IEEE
14 years 18 days ago
A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins
Abstract— We applied Support Vector Machines to the prediction of the subcellular localization of transmembrane proteins, and compared the performance of different sequence kerne...
Stefan Maetschke, Marcus Gallagher, Mikael Bod&eac...
ICML
2005
IEEE
14 years 7 months ago
The cross entropy method for classification
We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term ...
Shie Mannor, Dori Peleg, Reuven Y. Rubinstein
SPE
2002
119views more  SPE 2002»
13 years 5 months ago
HARTEX - a safe real-time kernel for distributed computer control systems
: The paper presents a hard real-time kernel for distributed computer control systems (DCCS) highlighting a number of novel features, such as integrated scheduling of hard and soft...
C. K. Angelov, I. E. Ivanov, Alan Burns
ISCA
2008
IEEE
148views Hardware» more  ISCA 2008»
14 years 20 days ago
Atomic Vector Operations on Chip Multiprocessors
The current trend is for processors to deliver dramatic improvements in parallel performance while only modestly improving serial performance. Parallel performance is harvested th...
Sanjeev Kumar, Daehyun Kim, Mikhail Smelyanskiy, Y...
JMLR
2008
116views more  JMLR 2008»
13 years 6 months ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li