近似最长递增子序列长度的流算法下界

A. Gál, Parikshit Gopalan
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引用次数: 73

摘要

我们表明,任何确定性数据流算法,在输入上进行常数次传递,并给出长度为n的序列中最长的递增子序列长度的常数因子近似值,必须使用空间Omega(radicn)。这证明了Gopalan, Jayram, Krauthgamer和Kumar[10]提出的一个猜想,他们证明了一个匹配的上界。我们的结果产生了所有近似因子的渐近紧塔界,从而解决了他们论文中主要的开放问题。我们的证明是基于分析一个相关的通信问题,并证明了它的一个直接和型性质。
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Lower Bounds on Streaming Algorithms for Approximating the Length of the Longest Increasing Subsequence
We show that any deterministic data-stream algorithm that, makes a constant number of passes over the input and gives a constant, factor approximation of the length of the longest increasing subsequence in a sequence of length n must use space Omega(radicn). This proves a conjecture made by Gopalan, Jayram, Krauthgamer and Kumar |10| who proved a matching upper bound. Our results yield asymptotically tight tower bounds for all approximation factors, thus resolving the main open problem, from their paper. Our proof is based on analyzing a related communication problem and proving a direct sum type property for it.
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