2 citations · 3 across the 6 of their papers we have counts for
6 papers
VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates
Guillaume Braun, Masashi Sugiyama
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 interact…
Strong Consistency Guarantees for Clustering High-Dimensional Bipartite Graphs with the Spectral Method
Guillaume Braun
In this work, we focus on the Bipartite Stochastic Block Model (BiSBM), a popular model for bipartite graphs with a community structure. We consider the high dimensional setting wh…
Minimax Optimal Clustering of Bipartite Graphs with a Generalized Power Method
Guillaume Braun, Hemant Tyagi
Clustering bipartite graphs is a fundamental task in network analysis. In the high-dimensional regime where the number of rows and the number of columns of the associat…
Seeded graph matching for the correlated Gaussian Wigner model via the projected power method
Ernesto Araya, Guillaume Braun, Hemant Tyagi
In the \emph{graph matching} problem we observe two graphs and the goal is to find an assignment (or matching) between their vertices such that some measure of edge agreement…
An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guarantees
Guillaume Braun, Hemant Tyagi, Christophe Biernacki
Real-world networks often come with side information that can help to improve the performance of network analysis tasks such as clustering. Despite a large number of empirical and…
Clustering multilayer graphs with missing nodes
Guillaume Braun, Hemant Tyagi, Christophe Biernacki
Relationship between agents can be conveniently represented by graphs. When these relationships have different modalities, they are better modelled by multilayer graphs where each…