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Titlebook: Nonlinear Optimization; Francisco J. Aragón,Miguel A. Goberna,Margarita M. Textbook 2019 Springer Nature Switzerland AG 2019 convexity.coe

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發(fā)表于 2025-3-23 13:32:46 | 只看該作者
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發(fā)表于 2025-3-23 15:59:19 | 只看該作者
Francisco J. Aragón,Miguel A. Goberna,Marco A. López,Margarita M. L. Rodrígueze characteristics of effective and equitable forms of participation, and acknowledge the significance of participation for promoting capabilities of intrinsic and instrumental value for development. They also explore the ways in which the capability approach can contribute to a . to guide participat
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發(fā)表于 2025-3-23 18:49:42 | 只看該作者
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發(fā)表于 2025-3-24 02:09:48 | 只看該作者
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發(fā)表于 2025-3-24 05:39:00 | 只看該作者
Francisco J. Aragón,Miguel A. Goberna,Marco A. López,Margarita M. L. Rodríguezvance: technology is crucial to justice and development chal.The capability approach of Martha Nussbaum and Amartya Sen places human capabilities at the centre stage of discussions about justice, equality, development and the quality of life. It rejects too much emphasis on mere preference satisfact
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發(fā)表于 2025-3-24 10:32:25 | 只看該作者
vance: technology is crucial to justice and development chal.The capability approach of Martha Nussbaum and Amartya Sen places human capabilities at the centre stage of discussions about justice, equality, development and the quality of life. It rejects too much emphasis on mere preference satisfact
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發(fā)表于 2025-3-24 12:22:13 | 只看該作者
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發(fā)表于 2025-3-24 18:52:42 | 只看該作者
Convexityduce a class of functions that are very useful in optimization, the convex functions, for which the local minima are also global minima. We begin with functions of one variable and follow with functions of several variables (or multivariate). The chapter finishes with the study of two particular cla
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發(fā)表于 2025-3-24 22:26:32 | 只看該作者
Unconstrained Optimizationonstraint set (typically . or .) and . is the objective function. Unconstrained optimization problems have been widely used in astronomy and engineering. On the one hand, data fitting by least squares was a method developed by astronomers as Laplace and Gauss, in the second half of the eighteenth ce
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發(fā)表于 2025-3-25 00:03:06 | 只看該作者
Convex Optimizationases of problem . in?(.): (a) ., where the constraint set . represents a given convex subset of . (as .). (b) ., where .with ., ., and . are affine functions for all .. In this case, . is a polyhedral convex set (an affine manifold in the particular case where . is the solution set of a system of li
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