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We propose Twin SVM, a binary SVM classifier that determines two nonparallel planes by solving two related SVM-type problems, each of which is smaller than in a conventional SVM. The Twin SVM formulation is in the spirit of proximal SVMs via generalized eigenvalues. On several benchmark data sets, Twin SVM is not only fast, but shows good generalization.(More)
A dual for linear programming problems with fuzzy parameters is introduced and it is shown that a two person zero sum matrix game with fuzzy pay-o(s is equivalent to a primal-dual pair of such fuzzy linear programming problems. Further certain di6culties with similar studies reported in the literature are discussed.
In this paper, we use the approach of adaptive critic design (ACD) for control, specifically, the action-dependent heuristic dynamic programming (ADHDP) method. A least squares support vector machine (SVM) regressor has been used for generating the control actions, while an SVM-based tree-type neural network (NN) is used as the critic. After a failure(More)
Traditional support vector machines (SVMs) assign data points to one of two classes, represented in the pattern space by two disjoint half-spaces. In this paper, we propose a fuzzy extension to proximal SVMs, where a fuzzy membership is assigned to each pattern, and points are classi1ed by assigning them to the nearest of two parallel planes that are kept(More)