## Abstract

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)) (_{2}^{n}) upper bound and a nearly matching 0.32 (_{2}^{n}) 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).

Original language | English |
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Pages (from-to) | 197-206 |

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 |