We obtain new separation results for the two-party external information complexity of boolean functions. The external information complexity of a function $f(x,y)$ is the minimum amount of information a two-party protocol computing $f$ must reveal to an outside observer about the input. We obtain the following results: 1. We prove an exponential separation between external and internal information complexity, which is the best possible; previously no separation was known. 2. We prove a near-quadratic separation between amortized zero-error communication complexity and external information complexity for total functions, disproving a conjecture of \cite{Bravermansurvey}. 3. We prove a matching upper showing that our separation result is tight.
翻译:我们从布林功能的两方外部信息复杂性中获得了新的分离结果。 功能美元( y) 的外部信息复杂性是计算投入的两方协议必须向外部观察者披露的最低信息量。 我们得到了以下结果: 1. 我们证明外部信息复杂性和内部信息复杂性是指数分解的,这是最好的; 之前没有知道分离。 2. 我们证明,对总功能而言,分解的零载通信复杂性和外部信息复杂性是近赤道分解的,对\ cite{Bravermansurvey}的推测是否定的。 3. 我们证明,我们的分离结果十分接近。