Information Cost Tradeoffs for Augmented Index and Streaming Language Recognition

Amit Chakrabarti, Graham Cormode, Ranganath Kondapally, A. Mcgregor
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引用次数: 32

Abstract

This paper makes three main contributions to the theory of communication complexity and stream computation. First, we present new bounds on the information complexity of AUGMENTED-INDEX. In contrast to analogous results for INDEX by Jain, Radhakrishnan and Sen [J. ACM, 2009], we have to overcome the significant technical challenge that protocols for AUGMENTED-INDEX may violate the ``rectangle property'' due to the inherent input sharing. Second, we use these bounds to resolve an open problem of Magniez, Mathieu and Nayak [STOC, 2010] on the multi-pass complexity of recognizing Dyck languages. This results in a natural separation between the standard multi-pass model and the multi-pass model that permits reverse passes. Third, we present the first passive memory checkers that verify the interaction transcripts of priority queues, stacks, and double-ended queues. We obtain tight upper and lower bounds for these problems, thereby addressing an important sub-class of the memory checking framework of Blum et al. [Algorithmica, 1994].
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增强索引与流语言识别的信息成本权衡
本文在通信复杂性和流计算理论方面做出了三个主要贡献。首先,给出了增广索引信息复杂度的新边界。与Jain, Radhakrishnan和Sen对INDEX的类似结果相反[J]。ACM, 2009],我们必须克服一个重大的技术挑战,即由于固有的输入共享,增强索引协议可能违反“矩形属性”。其次,我们使用这些边界来解决Magniez, Mathieu和Nayak [STOC, 2010]关于识别Dyck语言的多通道复杂性的开放问题。这导致了标准多通道模型和允许反向通道的多通道模型之间的自然分离。第三,我们提出了第一个被动内存检查器,用于验证优先级队列、堆栈和双端队列的交互记录。我们获得了这些问题的紧上界和下界,从而解决了Blum等人[Algorithmica, 1994]的内存检查框架的一个重要子类。
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