2 citations · 2 across the 7 of their papers we have counts for
9 papers
Normalized Likelihood Criteria for Model Selection in the Stochastic Block Model
Andressa Cerqueira, Felipe Baptistão
Estimating the number of communities is a fundamental problem in network analysis under the stochastic block model (SBM). In this paper, we study penalized estimators for this task…
Counting communities in weighted Stochastic Block Models via semidefinite programming
Deborah Oliveira, Andressa Cerqueira, Roberto Oliveira
We consider the problem of estimating the number of communities in a weighted balanced Stochastic Block Model. We construct hypothesis tests based on semidefinite programming and w…
Optimal recovery by maximum and integrated conditional likelihood in the general Stochastic Block Model
Andressa Cerqueira, Florencia Leonardi
In this paper, we obtain new results on the weak and strong consistency of the maximum and integrated conditional likelihood estimators for the community detection problem in the S…
A pseudo-likelihood approach to community detection in weighted networks
Andressa Cerqueira, Elizaveta Levina
Community structure is common in many real networks, with nodes clustered in groups sharing the same connections patterns. While many community detection methods have been develope…
Consistent model selection for the Degree Corrected Stochastic Blockmodel
Andressa Cerqueira, Sandro Gallo, Florencia Leonardi +1
The Degree Corrected Stochastic Block Model (DCSBM) was introduced by \cite{karrer2011stochastic} as a generalization of the stochastic block model in which vertices of the same co…
Graphical Construction of Spatial Gibbs Random Graphs
Andressa Cerqueira, Nancy L. Garcia
We consider a Random Graph Model on that incorporates the interplay between the statistics of the graph and the underlying space where the vertices are located. Ba…
Strong consistency of Krichevsky-Trofimov estimator for the number of communities in the Stochastic Block Model
Andressa Cerqueira, Florencia Leonardi
In this paper we introduce an estimator for the number of communities in the Stochastic Block Model (SBM), based on the maximization of a penalized version of the so-called Krichev…
A note on perfect simulation for exponential random graph models
Andressa Cerqueira, Aurélien Garivier, Florencia Leonardi
In this paper we propose a perfect simulation algorithm for the Exponential Random Graph Model, based on the Coupling From The Past method of Propp & Wilson (1996). We use a Glaube…
A test of hypotheses for random graph distributions built from EEG data
Andressa Cerqueira, Daniel Fraiman, Claudia D. Vargas +1
The theory of random graphs is being applied in recent years to model neural interactions in the brain. While the probabilistic properties of random graphs has been extensively stu…