ENTROPY OF SOME MODELS OF SPARSE RANDOM GRAPHS WITH VERTEX-NAMES

Author:

Aldous David J.,Ross Nathan

Abstract

Consider the setting of sparse graphs on N vertices, where the vertices have distinct “names”, which are strings of length O(log N) from a fixed finite alphabet. For many natural probability models, the entropy grows as c N log N for some model-dependent rate constant c. The mathematical content of this paper is the (often easy) calculation of c for a variety of models, in particular for various standard random graph models adapted to this setting. Our broader purpose is to publicize this particular setting as a natural setting for future theoretical study of data compression for graphs, and (more speculatively) for discussion of unorganized versus organized complexity.

Publisher

Cambridge University Press (CUP)

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Statistics, Probability and Uncertainty,Statistics and Probability

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Universal Lossless Compression Method Applicable to Sparse Graphs and Heavy–Tailed Sparse Graphs;IEEE Transactions on Information Theory;2023-02

2. A Universal Low Complexity Compression Algorithm for Sparse Marked Graphs;IEEE Journal on Selected Areas in Information Theory;2022-12

3. A Universal Lossless Compression Method applicable to Sparse Graphs and heavy-tailed Sparse Graphs;2021 IEEE International Symposium on Information Theory (ISIT);2021-07-12

4. Symmetry and the Entropy of Small-World Structures and Graphs;2021 IEEE International Symposium on Information Theory (ISIT);2021-07-12

5. On lossy Compression of Directed Graphs;IEEE Transactions on Information Theory;2021

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