Tight query complexity bounds for learning graph partitions
Abstract
Given a partition of a graph into connected components, the membership oracle asserts whether any two vertices of the graph lie in the same component or not. We prove that for , learning the components of an -vertex hidden graph with components requires at least membership queries. Our result improves on the best known information-theoretic bound of queries, and exactly matches the query complexity of the algorithm introduced by [Reyzin and Srivastava, 2007] for this problem. Additionally, we introduce an oracle, with access to which one can learn the number of components of in asymptotically fewer queries than learning the full partition, thus answering another question posed by the same authors. Lastly, we introduce a more applicable version of this oracle, and prove asymptotically tight bounds of queries for both learning and verifying an -edge hidden graph using it.
Keywords
Cite
@article{arxiv.2112.07897,
title = {Tight query complexity bounds for learning graph partitions},
author = {Xizhi Liu and Sayan Mukherjee},
journal= {arXiv preprint arXiv:2112.07897},
year = {2022}
}
Comments
Accepted for presentation at the 35th Annual Conference of Learning Theory, 2022