Learning a Hidden Subgraph

We consider the problem of learning a labeled graph from a given family of graphs on n vertices in a model where the only allowed operation is to query whether a set of vertices induces an edge. Questions of this type are motivated by problems in molecular biology. In the deterministic nonadaptive setting, we prove nearly matching upper and lower bounds for the minimum possible number of queries required when the family is the family of all stars of a given size or all cliques of a given size. We further describe some bounds that apply to general graphs.

• Type: Conference
• Year: 2004
• Where: ICALP
• Authors: Noga Alon, Vera Asodi
• Keywords: Deterministic Nonadaptive Setting, ICALP 2004, Labeled Graph, Minimum Possible Number, Theoretical Computer Science