The value of information-theoretic content of help bits for computation

Salman Beigi, O. Etesami, A. Gohari
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Abstract

“Help bits” are some limited trusted information about an instance or instances of a computational problem that may reduce the computational complexity of solving that instance or instances. Assume that we can efficiently solve k instances of a decision problem using some help bits whose entropy is less than k when the k instances are drawn independently from a particular distribution. Then there is an upper bound on the average-case complexity of the problem, namely we can efficiently solve an instance drawn from that distribution correctly with probability better than 1/2.
计算帮助位的信息论内容价值
“帮助位”是关于计算问题的一个或多个实例的一些有限的可信信息,可以降低解决该实例或多个实例的计算复杂性。假设当k个实例独立于特定分布时,我们可以使用熵小于k的帮助位有效地解决决策问题的k个实例。然后,问题的平均情况复杂性有一个上限,即我们可以有效地解决从该分布中正确抽取的实例,概率大于1/2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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