Abstract
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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Alon, N., Asodi, V. (2004). Learning a Hidden Subgraph. In: Díaz, J., Karhumäki, J., Lepistö, A., Sannella, D. (eds) Automata, Languages and Programming. ICALP 2004. Lecture Notes in Computer Science, vol 3142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27836-8_12
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DOI: https://doi.org/10.1007/978-3-540-27836-8_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22849-3
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