I started my PhD in applied mathematics in October 2017, under the supervision of Julien Jacques and Christophe Biernacki. The aim of the PhD thesis is to work on co-clustering techniques, and specifically with heterogeneous data (data of different kinds).
- Analysing health quality survey using constrained co-clustering model for ordinal data and some dynamic implication, to appear in Journal of the Royal Statistical Society, Series C pdf.
- Model-based co-clustering for mixed type data: pre-print pdf.
- ordinalClust: a package for analyzing ordinal data: pre-print pdf.
- Self-Organised Co-clustering for textual data synthesis pre-print pdf.
- ordinalClust, a package for classification, clustering and co-clustering of ordinal data: CRAN.
- (soon online): CpDyna, a package for clustering dynamic networks and detection of multiple change points. . This is a joint work with Marco Corneli.
- (soon online): mixedClust, an R package for classification, clustering and co-clustering of mixed data.
- (soon online): SOCC, an R package for textual data synthesis through co-clustering.
- ordinalClust, an R package for analyzing ordinal data, useR 2019, Toulouse, France.
- Tri-clustering pourdonnées de comptage, 51èmes Journées des Statistiques, Nancy 2019, France.
- Analyzing large matrices of ordinal data, CMStatistics 2018, Pisa, Italy.
- Co-clustering de données textuelles et continues, 50èmes Journées des Statistiques, EDF Lab Paris Saclay 2018, France.
- mixedClust, an R package for classification, clustering and co-clustering of mixed data, Model based Working-group 2018, Ann-Arbor, USA.
- Dynamic Constrained Co-clustering on ordinal data, Statlearn 2018, Nice, France.
- Dynamic Constrained Co-clustering on ordinal data, Model based Working-group 2017, Perugia, Italy.