Titlebook: Generalized Convexity and Generalized Monotonicity; Proceedings of the 6 Nicolas Hadjisavvas,Juan Enrique Martínez-Legaz,Je Conference proc

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書目名稱Generalized Convexity and Generalized Monotonicity影響因子(影響力)




書目名稱Generalized Convexity and Generalized Monotonicity影響因子(影響力)學科排名




書目名稱Generalized Convexity and Generalized Monotonicity網(wǎng)絡公開度




書目名稱Generalized Convexity and Generalized Monotonicity網(wǎng)絡公開度學科排名




書目名稱Generalized Convexity and Generalized Monotonicity被引頻次




書目名稱Generalized Convexity and Generalized Monotonicity被引頻次學科排名




書目名稱Generalized Convexity and Generalized Monotonicity年度引用




書目名稱Generalized Convexity and Generalized Monotonicity年度引用學科排名




書目名稱Generalized Convexity and Generalized Monotonicity讀者反饋




書目名稱Generalized Convexity and Generalized Monotonicity讀者反饋學科排名

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Discrete Higher Order Convex Functions and their Applicationsrandom variables involved are discrete. We look for the minimum or maximum of a linear functional acting on an unknown probability distribution subject to a finite number of moment constraints. Using linear programming methodology, we present structural theorems, in both the univariate and multivari

Omnipotent

Cuts and Semidefinite Relaxations for Nonconvex Quadratic Problemsedure can be applied for generating tighter positive semidefinite relaxations. Computational results indicate that the relative gap obtained by the relaxations is less than 1% when the number of variables is up to 100. We also show a branch and bound procedure for obtaining an exact solution of the

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The Steiner Ratio of ,y”, that means, given a finite set . of points in the plane, search for a network interconnecting these points with minimal length. This shortest network must be a tree and is called a Steiner Minimal Tree (SMT). It may contain vertices different from the points which axe to be connected. Such point

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Normal Cones to Sublevel Sets: An Axiomatic Approach the definition given in [.] (resp. [.]) is recovered. Moreover, the results obtained in [.] are extended in this more general setting. Under mild assumptions, quasiconvex continuous functions are classified, establishing an equivalence relation between functions with the same normal operator. Appli

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First and Second Order Characterizations of a Class of Pseudoconcave Vector Functionsoncavity and scalar strict pseudoconcavity, as well as the optimality properties of these functions, such as the global optimality of local optima, of critical points and of points verifying Kuhn-Tucker conditions. The considered functions come out to be particularly relevant since it is possible fo

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