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An information statistics approach to data stream and communication complexity

Ziv Bar-Yossef, +3 more
- Vol. 68, Iss: 4, pp 209-218
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TLDR
This work presents a new method for proving strong lower bounds in communication complexity based on the notion of the conditional information complexity of a function, and shows that it also admits a direct sum theorem.
Abstract
We present a new method for proving strong lower bounds in communication complexity. This method is based on the notion of the conditional information complexity of a function which is the minimum amount of information about the inputs that has to be revealed by a communication protocol for the function. While conditional information complexity is a lower bound on the communication complexity, we show that it also admits a direct sum theorem. Direct sum decomposition reduces our task to that of proving (conditional) information complexity lower bounds for simple problems (such as the AND of two bits). For the latter, we develop novel techniques based on Hellinger distance and its generalizations.

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Citations
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Journal ArticleDOI

Data streams: algorithms and applications

TL;DR: Data Streams: Algorithms and Applications surveys the emerging area of algorithms for processing data streams and associated applications, which rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity.
Book

Data Streams: Algorithms and Applications

TL;DR: In this paper, the authors present a survey of basic mathematical foundations for data streaming systems, including basic mathematical ideas, basic algorithms, and basic algorithms and algorithms for data stream processing.
Journal ArticleDOI

Index Coding With Side Information

TL;DR: A measure on graphs, the minrank, is identified, which exactly characterizes the minimum length of linear and certain types of nonlinear INDEX codes and for natural classes of side information graphs, including directed acyclic graphs, perfect graphs, odd holes, and odd anti-holes, minrank is the optimal length of arbitrary INDex codes.
Journal ArticleDOI

Asymptotics in Statistics–Some Basic Concepts

TL;DR: In this article, the convergence of Distri butions of Likelihood Ratio has been discussed, and the authors propose a method to construct a set of limit laws for Likelihood Ratios.
Proceedings ArticleDOI

Index Coding with Side Information

TL;DR: A measure on graphs, the minrank, is identified, which exactly characterizes the minimum length of linear and certain types of nonlinear INDEX codes and for natural classes of side information graphs, including directed acyclic graphs, perfect graphs, odd holes, and odd anti-holes, minrank is the optimal length of arbitrary INDex codes.
References
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Book

Elements of information theory

TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Journal ArticleDOI

Graph-Based Algorithms for Boolean Function Manipulation

TL;DR: In this paper, the authors present a data structure for representing Boolean functions and an associated set of manipulation algorithms, which have time complexity proportional to the sizes of the graphs being operated on, and hence are quite efficient as long as the graphs do not grow too large.
Journal ArticleDOI

Divergence measures based on the Shannon entropy

TL;DR: A novel class of information-theoretic divergence measures based on the Shannon entropy is introduced, which do not require the condition of absolute continuity to be satisfied by the probability distributions involved and are established in terms of bounds.
Book

Communication Complexity

TL;DR: This chapter surveys the theory of two-party communication complexity and presents results regarding the following models of computation: • Finite automata • Turing machines • Decision trees • Ordered binary decision diagrams • VLSI chips • Networks of threshold gates.