ECCC-Report TR19-083https://eccc.weizmann.ac.il/report/2019/083Comments and Revisions published for TR19-083en-usTue, 28 Sep 2021 18:58:46 +0300
Revision 2
| Testing Graphs against an Unknown Distribution |
Lior Gishboliner,
Asaf Shapira
https://eccc.weizmann.ac.il/report/2019/083#revision2The 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.Tue, 28 Sep 2021 18:58:46 +0300https://eccc.weizmann.ac.il/report/2019/083#revision2
Revision 1
| Testing Graphs against an Unknown Distribution |
Lior Gishboliner,
Asaf Shapira
https://eccc.weizmann.ac.il/report/2019/083#revision1The 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.Wed, 12 Jun 2019 22:30:17 +0300https://eccc.weizmann.ac.il/report/2019/083#revision1
Paper TR19-083
| Testing Graphs against an Unknown Distribution |
Lior Gishboliner,
Asaf Shapira
https://eccc.weizmann.ac.il/report/2019/083The 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.Wed, 05 Jun 2019 00:17:16 +0300https://eccc.weizmann.ac.il/report/2019/083