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Showing 1 to 5 of 5 for “"Space Dilation"”.
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Limited Memory Space Dilation and Reduction Algorithms
… This well known r-algorithm, which employs a space dilation strategy in the direction of the difference between two successive subgradients, is recognized as being one of the most effective procedures for solving nondifferentiable optimization problems. However, the method needs to store the …
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Linear and ellipsoidal pattern separation: theoretical aspects and experimental analysis
… data separation in some Euclidean feature space. The task is to infer a classifier (a separating surface) from a set or sequence of observations. This classifier would later be used to discern observations of different types. In this work, the classification problem is viewed from the …
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A primal-dual conjugate subgradient algorithm for large- scale/specially structured linear programming problems
… improve the performance of the algorithm include space-dilation and box step techniques, pattern search strategies and suboptimization based on complementary slackness conditions. The algorithm is tested on three different transportation problems with additional constraints which are faced by the …
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Nondifferentiable optimization algorithms with application to solving Lagrangian dual problems
… bounds on an optimum or regarding the solution space. In practice, the step-length is often calculated by using an estimate of the optimal objective function value. For general nondifferentiable optimization problems, however, this may not be readily available. Hence, we design an algorithm that …
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Nondifferentiable Optimization of Lagrangian Dual Formulations for Linear Programs with Recovery of Primal Solutions
… LP relaxations, sometimes in higher dimensional spaces, are widely used for bounding and cut-generation purposes. Often, such relaxations turn out to be large-sized, ill-conditioned problems for which simplex as well as interior point based methods can tend to be ineffective. In contrast, …