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» The LCCP for Optimizing Kernel Parameters for SVM
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BMCBI
2008
143views more  BMCBI 2008»
14 years 9 months ago
Automatic detection of exonic splicing enhancers (ESEs) using SVMs
Background: Exonic splicing enhancers (ESEs) activate nearby splice sites and promote the inclusion (vs. exclusion) of exons in which they reside, while being a binding site for S...
Britta Mersch, Alexander Gepperth, Sándor S...
ICML
2007
IEEE
15 years 10 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro
ICPR
2008
IEEE
15 years 10 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
IDEAL
2004
Springer
15 years 2 months ago
Kernel Density Construction Using Orthogonal Forward Regression
Abstract— The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model gener...
Sheng Chen, Xia Hong, Chris J. Harris
ICML
2004
IEEE
15 years 10 months ago
Multi-task feature and kernel selection for SVMs
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
Tony Jebara