Titlebook: Optimization and Its Applications in Control and Data Sciences; In Honor of Boris T. Boris Goldengorin Book 2016 Springer International Pub

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Lagrangian Duality in Complex Pose Graph Optimization,ly no known technique can guarantee the efficient computation of a global optimal solution. In this paper, we show that Lagrangian duality allows computing a globally optimal solution, under certain conditions that are satisfied in many practical cases. Our first contribution is to frame the PGO pro

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Matrix-Free Convex Optimization Modeling, user into an equivalent cone program in a way that preserves fast linear transforms in the original problem. By representing linear functions in the transformation process not as matrices, but as graphs that encode composition of linear operators, we arrive at a matrix-free cone program, i.e., one

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Nonparametric Ellipsoidal Approximation of Compact Sets of Random Points,ximations of such sets are ellipsoids. B.T. Polyak and his disciples use two kinds of ellipsoids covering a set of points—minimal volume ellipsoids and minimal trace ellipsoids. We propose a way to construct an ellipsoidal approximation of an attainability set using nonparametric estimations. These

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Applying the Gradient Projection Method to a Model of Proportional Membership for Fuzzy Cluster Anay express an extent of each prototype, which makes its criterion to loose the conventional prototype-additive structure. The methods for fitting the model at different fuzziness parameter values are presented. Because of the complexity of the clustering criterion, minimization of the errors requires

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