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» Optimization on Support Vector Machines
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PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
15 years 4 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
PAKDD
2007
ACM
128views Data Mining» more  PAKDD 2007»
15 years 4 months ago
Selecting a Reduced Set for Building Sparse Support Vector Regression in the Primal
Recent work shows that Support vector machines (SVMs) can be solved efficiently in the primal. This paper follows this line of research and shows how to build sparse support vector...
Liefeng Bo, Ling Wang, Licheng Jiao
PARLE
1994
15 years 1 months ago
Run-Time Optimization of Sparse Matrix-Vector Multiplication on SIMD Machines
Sparse matrix-vector multiplication forms the heart of iterative linear solvers used widely in scientific computations (e.g., finite element methods). In such solvers, the matrix-v...
Louis H. Ziantz, Can C. Özturan, Boleslaw K. ...
ESA
2010
Springer
227views Algorithms» more  ESA 2010»
14 years 11 months ago
Approximating Parameterized Convex Optimization Problems
We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an -approximat...
Joachim Giesen, Martin Jaggi, Sören Laue
NIPS
2000
14 years 11 months ago
Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
A system has been developed to extract diagnostic information from jet engine carcass vibration data. Support Vector Machines applied to novelty detection provide a measure of how...
Paul Hayton, Bernhard Schölkopf, Lionel Taras...