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Titlebook: Nonsmooth Optimization and Related Topics; F. H. Clarke,V. F. Dem’yanov,F. Giannessi Book 1989 Springer Science+Business Media New York 19

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P. D. Loewend to make a link between what I was telling you last week with regard to Socrates and the . and what I will tell you next week with regard to the Cynics. That is to say, I will speak to you about the . Before this, a short comment [concerning, first,] what I was telling you about Dumézil’s book and,
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A. Miele,T. Wange . approximation. It was shown that the discrete wave dynamics consisting of the interaction of . and . leads to the existence of two different eigenvalue branches in the spectrum: an . one, of physical nature, and an . one, of spurious nature. The fact that both . have critical points where the co
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J. Morgano speed-up computations by a multiresolution representation of the numerical solution on adaptive grids which are introduced by suitable thresholding of its wavelet coefficients. Further speed-up is obtained by the combination of the multiresolution scheme with an adaptive strategy for time integrat
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R. Orlandoni,O. Petrucci,M. Tosquesume). The significance of somatic investigation is exemplified by mortality rates of 18% (Theander 1985), a third of which is due to suicide and about two thirds directly and indirectly related to somatic complications of anorexia (Andersen et al. 1990). Besides psychiatric comorbidity, somatic comp
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Compactness and Boundedness for a Class of Concave-Convex Functions, specifically, we are concerned here with concave-convex functions defined on finite dimensional spaces with values in the extended real line: the main result is Compactness Theorem 4.2, which allows us to give sufficient conditions in order to obtain the closure of epi-hypo limits by means of the p
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Applications of Proximal Subgradients,cular seen broad application in optimization and elsewhere. Of late, one of the most active areas of study has been proximal normal analysis. Although the proximal normal concept was actually at the heart of the very first definitions of the generalized gradient and normal cone [5], [6], it was not
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On Cone Approximations and Generalized Directional Derivatives,en optimization problems connected with real life problems have a “nondifferentiable” structure. Hence it is useful to develop appropriate notions of generalized differentiability in order to obtain analogous optimality conditions in nondifferentiable case, too. The concepts of the directional deriv
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