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

机译:帮助位的信息理论内容的计算价值

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摘要

“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.
机译:“帮助位”是有关一个或多个计算问题的一个或多个实例的有限的受信任信息,可以降低解决一个或多个实例的计算复杂性。假设当独立于特定分布绘制k个实例时,我们可以使用熵小于k的一些帮助位来有效地解决k个决策问题实例。然后,问题的平均情况复杂度有一个上限,即我们可以有效地从概率分布中正确解出一个实例,概率大于1/2。

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