Learning a hidden graph

Abstract

We study the problem of learning a hidden graph by edge-detecting queries, each of which tells whether a set of vertices induces an edge of the hidden graph or not. We provide a new information-theoretic lower bound and give a more efficient adaptive algorithm to learn a general graph with n vertices and m edges in m log n + 10m + 3n edge-detecting queries.