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CORR
2008
Springer
142views Education» more  CORR 2008»
13 years 7 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev
JMLR
2006
105views more  JMLR 2006»
13 years 7 months ago
Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems
Parallel software for solving the quadratic program arising in training support vector machines for classification problems is introduced. The software implements an iterative dec...
Luca Zanni, Thomas Serafini, Gaetano Zanghirati
FSS
2007
102views more  FSS 2007»
13 years 7 months ago
Extraction of fuzzy rules from support vector machines
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...
CORR
2010
Springer
179views Education» more  CORR 2010»
13 years 4 months ago
Comparison of Support Vector Machine and Back Propagation Neural Network in Evaluating the Enterprise Financial Distress
Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back prop...
Ming-Chang Lee, To Chang
ICPR
2008
IEEE
14 years 2 months ago
Fast model selection for MaxMinOver-based training of support vector machines
OneClassMaxMinOver (OMMO) is a simple incremental algorithm for one-class support vector classification. We propose several enhancements and heuristics for improving model select...
Fabian Timm, Sascha Klement, Thomas Martinetz