We consider the problem of clustering n items into K disjoint clusters using noisy answers
from crowdsourced workers to pairwise queries of the type:“Are items i and j from the same …

We study graph clustering in the Stochastic Block Model (SBM) in the presence of both large
clusters and small, unrecoverable clusters. Previous convex relaxation approaches …

Social networks are often associated with rich side information, such as texts and images.
While numerous methods have been developed to identify communities from pairwise …

We study graph clustering in the Stochastic Block Model (SBM) in the presence of both large
clusters and small, unrecoverable clusters. Previous approaches achieving exact recovery …

Recovering the underlying clustering of a set $ U $ of $ n $ points by asking pair-wise same-
cluster queries has garnered significant interest in the last decade. Given a query $ S\subset …

Community detection in the stochastic block model is one of the central problems of graph
clustering. Since its introduction by Holland, Laskey, and Leinhardt (Social Networks, 1983) …

Many methods are applied to network surveillance for anomaly detection. Some quality
control methods have been developed to monitor several quality characteristics …

Unsupervised clustering algorithms for vectors has been widely used in the area of machine
learning. Many applications, including the biological data we studied in this paper, contain …