2 citations · 2 across the 2 of their papers we have counts for
4 papers
greed: An R Package for Model-Based Clustering by Greedy Maximization of the Integrated Classification Likelihood
Etienne Côme, Nicolas Jouvin
The greed package implements the general and flexible framework of arXiv:2002.11577 for model-based clustering in the R language. Based on the direct maximization of the exact Inte…
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering
Nicolas Jouvin, Charles Bouveyron, Pierre Latouche
High-dimensional data clustering has become and remains a challenging task for modern statistics and machine learning, with a wide range of applications. We consider in this work t…
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood
Etienne Côme, Nicolas Jouvin, Pierre Latouche +1
Finding a set of nested partitions of a dataset is useful to uncover relevant structure at different scales, and is often dealt with a data-dependent methodology. In this paper, we…
Greedy clustering of count data through a mixture of multinomial PCA
Nicolas Jouvin, Pierre Latouche, Charles Bouveyron +2
Count data is becoming more and more ubiquitous in a wide range of applications, with datasets growing both in size and in dimension. In this context, an increasing amount of work…