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dc.contributor.authorChang, Huilanen_US
dc.contributor.authorFu, Hung-Linen_US
dc.contributor.authorShih, Chih-Huaien_US
dc.date.accessioned2018-08-21T05:53:09Z-
dc.date.available2018-08-21T05:53:09Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1862-4472en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s11590-017-1131-zen_US
dc.identifier.urihttp://hdl.handle.net/11536/144339-
dc.description.abstractMotivated by applications in genome sequencing, Grebinski andKucherov (Discret Appl Math 88: 147-165, 1998) studied the graph learning problem which is to identify a hidden graph drawn from a given class of graphs with vertex set {1, 2,..., n} by edge-detecting queries. Each query tells whether a set of vertices induces any edge of the hidden graph or not. For the class of all hypergraphs whose edges have size at most r, Chodoriwsky and Moura (Theor Comput Sci 592: 1-8, 2015) provided an adaptive algorithm that learns the class in O(m(r) log n) queries if the hidden graph has m edges. In this paper, we provide an adaptive algorithm that learns the class of all r-uniform hypergraphs in mr log n + (6e)(r)m(r+1/2) queries if the hidden graph has m edges.en_US
dc.language.isoen_USen_US
dc.subjectGraph learningen_US
dc.subjectGroup testingen_US
dc.subjectComplex modelen_US
dc.subjectAdaptive algorithmen_US
dc.titleLearning a hidden uniform hypergraphen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s11590-017-1131-zen_US
dc.identifier.journalOPTIMIZATION LETTERSen_US
dc.citation.volume12en_US
dc.citation.spage55en_US
dc.citation.epage62en_US
dc.contributor.department應用數學系zh_TW
dc.contributor.departmentDepartment of Applied Mathematicsen_US
dc.identifier.wosnumberWOS:000419552800006en_US
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