We consider the problem of learning a matching (i.e., a graph in which all vertices have degree 0 or 1) in a model where the only allowed operation is to query whether a set of vertices induces an edge. This is motivated by a problem that arises in molecular biology. In the deterministic nonadaptive setting, we prove a (1/2 + o(1)) (2n) upper bound and a nearly matching 0.32 (2n) lower bound for the minimum possible number of queries. In contrast, if we allow randomness then we obtain (by a randomized, nonadaptive algorithm) a much lower O(n log n) upper bound, which is best possible (even for randomized fully adaptive algorithms).
|Number of pages||10|
|Journal||Annual Symposium on Foundations of Computer Science - Proceedings|
|State||Published - 2002|
|Event||The 34rd Annual IEEE Symposium on Foundations of Computer Science - Vancouver, BC, Canada|
Duration: 16 Nov 2002 → 19 Nov 2002