Czasopismo
Tytuł artykułu
Autorzy
Warianty tytułu
Języki publikacji
Abstrakty
In this paper, we consider the planted partition model, in which n = ks vertices of a random graph are partitioned into k “clusters,” each of size s. Edges between vertices in the same cluster and different clusters are included with constant probability p and q, respectively (where 0 ≤ q < p ≤ 1). We give an efficient algorithm that, with high probability, recovers the clusters as long as the cluster sizes are are least (√n). Informally, our algorithm constructs the projection operator onto the dominant k-dimensional eigenspace of the graph’s adjacency matrix and uses it to recover one cluster at a time. To our knowledge, our algorithm is the first purely spectral algorithm which runs in polynomial time and works even when s = Θ (√n), though there have been several non-spectral algorithms which accomplish this. Our algorithm is also among the simplest of these spectral algorithms, and its proof of correctness illustrates the usefulness of the Cauchy integral formula in this domain.
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Numer
Strony
139-157
Opis fizyczny
Daty
wydano
2017-01-26
otrzymano
2016-11-24
zaakceptowano
2017-07-14
online
2017-08-18
Twórcy
autor
- , Illinois 60607-7045,, scole3@uic.edu
autor
- , Illinois 60607-7045,, friedlan@uic.edu
autor
- , Illinois 60607-7045,, lreyzin@uic.edu
Bibliografia
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.doi-10_1515_spma-2017-0013