Estimating Parameters Associated with Monotone Properties

Medientyp: Sonstige Veröffentlichung; E-Artikel; Elektronischer Konferenzbericht

Titel: Estimating Parameters Associated with Monotone Properties

Beteiligte: Hoppen, Carlos [Verfasser:in]; Kohayakawa, Yoshiharu [Verfasser:in]; Lang, Richard [Verfasser:in]; Lefmann, Hanno [Verfasser:in]; Stagni, Henrique [Verfasser:in]

Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2016

Sprache: Englisch

DOI: https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2016.35

Schlagwörter: edit distance to monotone graph properties ; parameter estimation ; entropy of subgraph classes ; parameter testing ; speed of subgraph classes

Entstehung:

Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.

Beschreibung: There has been substantial interest in estimating the value of a graph parameter, i.e., of a real function defined on the set of finite graphs, by sampling a randomly chosen substructure whose size is independent of the size of the input. Graph parameters that may be successfully estimated in this way are said to be testable or estimable, and the sample complexity q_z=q_z(epsilon) of an estimable parameter z is the size of the random sample required to ensure that the value of z(G) may be estimated within error epsilon with probability at least 2/3. In this paper, we study the sample complexity of estimating two graph parameters associated with a monotone graph property, improving previously known results. To obtain our results, we prove that the vertex set of any graph that satisfies a monotone property P may be partitioned equitably into a constant number of classes in such a way that the cluster graph induced by the partition is not far from satisfying a natural weighted graph generalization of P}. Properties for which this holds are said to be recoverable, and the study of recoverable properties may be of independent interest.

Zugangsstatus: Freier Zugang

Nur in Feld suchen:

Zuletzt gesuchte Begriffe: