信息复杂性的张力界限
Tension Bounds for Information Complexity
摘要：
这项工作的主要贡献是将信息复杂性与“张力”联系起来[Prabhakaran and Prabhakaran，2014] --一个与协议无关的信息理论量--并说明它允许推导出信息复杂性的强下界。特别是，我们使用这种联系的一个非常特殊的情况，在信息复杂性和差异之间给出了一个比Braverman和Weinstein（2012）的工作（尽管仅限于独立输入）更紧密的定量联系。此外，由于张力实际上是一个多维概念，因此它使我们能够绑定表示2方协议中两个方向上的通信量之间的权衡的2维区域。这项工作也是为了强调张力作为一对随机变量之间的相关性的基本措施，与计算机科学和信息论中的各种问题有着丰富的联系。
英文摘要：
The main contribution of this work is to relate information complexity to "tension" [Prabhakaran and Prabhakaran, 2014] - an information-theoretic quantity defined with no reference to protocols - and to illustrate that it allows deriving strong lower-bounds on information complexity. In particular, we use a very special case of this connection to give a quantitatively tighter connection between information complexity and discrepancy than the one in the work of Braverman and Weinstein (2012) (albeit, restricted to independent inputs). Further, as tension is in fact a multi-dimensional notion, it enables us to bound the 2-dimensional region that represents the trade-off between the amounts of communication in the two directions in a 2-party protocol. This work is also intended to highlight tension as a fundamental measure of correlation between a pair of random variables, with rich connections to a variety of questions in computer science and information theory.
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