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- W3174618332 abstract "In [1] and [2] we developed a duality theory for multilinear norm inequalities. This duality theory is underpinned by a disentanglement theorem, which states that estimates on a weighted geometric mean over (convex) families of functions can be disentangled into quantitatively linked estimates on each family separately. The disentanglement theorem was proved in [1] via minimax theory together with weak*-compactness arguments in the space of finitely additive measures, and an application of the Yosida-Hewitt theory of such measures. In this paper we provide an alternate, rather elementary approach to the disentanglement theorem: we first prove a finite-dimensional case via perturbation and strong compactness, and then, building on that, the general infinite-dimensional case via the finite intersection property and weak compactness." @default.
- W3174618332 created "2021-07-05" @default.
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- W3174618332 date "2021-06-30" @default.
- W3174618332 modified "2023-09-27" @default.
- W3174618332 title "A variational proof of a disentanglement theorem for multilinear norm inequalities" @default.
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