50 citations · 73 across the 9 of their papers we have counts for
10 papers
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…
Model-based Clustering with Missing Not At Random Data
Aude Sportisse, Matthieu Marbac, Fabien Laporte +4
Model-based unsupervised learning, as any learning task, stalls as soon as missing data occurs. This is even more true when the missing data are informative, or said missing not at…
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…
Simultaneous semi-parametric estimation of clustering and regression
Matthieu Marbac, Mohammed Sedki, Christophe Biernacki +1
We investigate the parameter estimation of regression models with fixed group effects, when the group variable is missing while group related variables are available. This problem…
On the local and global properties of the gravitational spheres of influence
D. Souami, J. Cresson, C. Biernacki +1
We revisit the concept of sphere of gravitational activity, to which we give both a geometrical and physical meaning. This study aims to refine this concept in a much broader conte…
Feature quantization for parsimonious and interpretable predictive models
Adrien Ehrhardt, Christophe Biernacki, Vincent Vandewalle +1
For regulatory and interpretability reasons, logistic regression is still widely used. To improve prediction accuracy and interpretability, a preprocessing step quantizing both con…