Browsing by Subject "Linear programming."
Now showing items 1-9 of 9
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An analysis of some of the most useful quantitative methods relating to the controllership function /
(The University of Oklahoma., 1967) -
Decomposition techniques for support vector machines training and applications.
(2002)The theory of the Support Vector Machine (SVM) algorithm is based on statistical learning theory and can be applied to pattern recognition and regression. Training of SVMs leads to either a quadratic programming (QP) ... -
Least square multi-class kernel machines with prior knowledge and applications.
(2006)In this study, the problem of discriminating between objects of two or more classes with (or without) prior knowledge is investigated. We present how a two-class discrimination model with or without prior knowledge can be ... -
Polyhedral subspaces and the selection of optimal bases in probabilistic linear programming /
(The University of Oklahoma., 1972) -
A primal-dual algorithm for bounded variables with extensions to parametric analysis /
(The University of Oklahoma., 1970) -
Primal-dual techniques for nonlinear programming and applications to artificial neural network training.
(1997)In this work, new developments in primal-dual techniques for general constrained non-linear programming problems are proposed. We first implement a modified version of the general nonlinear primal-dual algorithm that was ... -
Synthesis of optimum linear multivariable systems /
(The University of Oklahoma., 1967) -
The time domain technique for linear system identification /
(The University of Oklahoma., 1965) -
Uncertainty and sensitivity analysis in support vector machines: Robust optimization and uncertain programming approaches.
(2006)Noisy or uncertain data are common in machine learning and data mining applications. Noisy data can significantly affect the behavior of data mining and machine learning algorithms. Robust optimization and sensitivity ...