Approximately Counting Embeddings into Random Graphs
Martin Furer, Shiva Prasad Kasiviswanathan

TL;DR
This paper introduces a novel graph decomposition technique enabling efficient approximation of subgraph counting in random graphs, covering broad classes of graphs including bounded-degree and planar graphs.
Contribution
It presents the first general subcase of subgraph isomorphism counting that is almost always efficiently approximable, using a new vertex labeling decomposition method.
Findings
Provides a simple randomized algorithm for counting embeddings.
Achieves a fully polynomial randomized approximation scheme for many graph classes.
Includes graphs of degree at most two, forests, grid graphs, and certain subclasses of planar graphs.
Abstract
Let H be a graph, and let C_H(G) be the number of (subgraph isomorphic) copies of H contained in a graph G. We investigate the fundamental problem of estimating C_H(G). Previous results cover only a few specific instances of this general problem, for example, the case when H has degree at most one (monomer-dimer problem). In this paper, we present the first general subcase of the subgraph isomorphism counting problem which is almost always efficiently approximable. The results rely on a new graph decomposition technique. Informally, the decomposition is a labeling of the vertices such that every edge is between vertices with different labels and for every vertex all neighbors with a higher label have identical labels. The labeling implicitly generates a sequence of bipartite graphs which permits us to break the problem of counting embeddings of large subgraphs into that of counting…
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