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Revision #2 to TR19-083 | 28th September 2021 18:58

Testing Graphs against an Unknown Distribution

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Revision #2
Authors: Lior Gishboliner, Asaf Shapira
Accepted on: 28th September 2021 18:58
Downloads: 265
Keywords: 


Abstract:

The area of graph property testing seeks to understand the relation between the global properties of a graph and its local statistics. In the classical model, the local statistics of a graph is defined relative to a uniform distribution over the graph’s vertex set. A graph property $\mathcal{P}$ is said to be testable if the local statistics of a graph can allow one to distinguish between graphs satisfying $\mathcal{P}$ and those that are far from satisfying it.

Goldreich recently introduced a generalization of this model in which one endows the vertex set of the input graph with an arbitrary and unknown distribution, and asked which of the properties that can be tested in the classical model can also be tested in this more general setting. We completely resolve this problem by giving a (surprisingly ``clean'') characterization of these properties. To this end, we prove a removal lemma for vertex weighted graphs which is of independent interest.


Revision #1 to TR19-083 | 12th June 2019 22:30

Testing Graphs against an Unknown Distribution





Revision #1
Authors: Lior Gishboliner, Asaf Shapira
Accepted on: 12th June 2019 22:30
Downloads: 573
Keywords: 


Abstract:

The area of graph property testing seeks to understand the relation between the global properties of a graph and its local statistics. In the classical model, the local statistics of a graph is defined relative to a uniform distribution over the graph’s vertex set. A graph property $\mathcal{P}$ is said to be testable if the local statistics of a graph can allow one to distinguish between graphs satisfying $\mathcal{P}$ and those that are far from satisfying it.

Goldreich recently introduced a generalization of this model in which one endows the vertex set of the input graph with an arbitrary and unknown distribution, and asked which of the properties that can be tested in the classical model can also be tested in this more general setting. We completely resolve this problem by giving a (surprisingly ``clean'') characterization of these properties. To this end, we prove a removal lemma for vertex weighted graphs which is of independent interest.


Paper:

TR19-083 | 4th June 2019 22:56

Testing Graphs against an Unknown Distribution





TR19-083
Authors: Lior Gishboliner, Asaf Shapira
Publication: 5th June 2019 00:17
Downloads: 630
Keywords: 


Abstract:

The area of graph property testing seeks to understand the relation between the global properties of a graph and its local statistics. In the classical model, the local statistics of a graph is defined relative to a uniform distribution over the graph’s vertex set. A graph property $\mathcal{P}$ is said to be testable if the local statistics of a graph can allow one to distinguish between graphs satisfying $\mathcal{P}$ and those that are far from satisfying it.

Goldreich recently introduced a generalization of this model in which one endows the vertex set of the input graph with an arbitrary and unknown distribution, and asked which of the properties that can be tested in the classical model can also be tested in this more general setting. We completely resolve this problem by giving a (surprisingly ``clean'') characterization of these properties. To this end, we prove a removal lemma for vertex weighted graphs which is of independent interest.



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