Learning a hidden matching

Noga Alon*, Richard Beigel, Simon Kasif, Steven Rudich, Benny Sudakovh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

57 Scopus citations


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))( n 2) upper bound and a nearly matching 0.32 ( n 2) 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 languageEnglish
Pages (from-to)487-501
Number of pages15
JournalSIAM Journal on Computing
Issue number2
StatePublished - Jan 2004


  • Combinatorial search problems
  • Finite protective planes
  • Genome sequencing
  • Matchings in graphs


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