设计概率支持映射熵域

J. Walsh, Alexander Erick Trofimoff
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引用次数: 1

摘要

熵域的边界已被证明可以决定网络编码、流、分布式存储和编码缓存等关键问题中的基本不等式和限制。该边界的未知部分需要非线性结构,而非线性结构反过来又可以通过其潜在概率分布的支持来参数化。认识到熵中的术语是子模块的,可以使这种支持的设计最大限度地向这个边界推进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Designing Probabilistic Supports to Map the Entropy Region
The boundary of the entropy region has been shown to determine fundamental inequalities and limits in key problems in network coding, streaming, distributed storage, and coded caching. The unknown part of this boundary requires nonlinear constructions, which can, in turn, be parameterized by the support of their underlying probability distributions. Recognizing that the terms in entropy are submodular enables the design of such supports to maximally push out towards this boundary.
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