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Randel, R., Aloise, D., & Hertz, A. (avril 2023). A Lagrangian-based approach to learn distance metrics for clustering with minimal data transformation [Communication écrite]. SIAM International Conference on Data Mining (SDM 2023), Minneapolis, MN, USA. Lien externe
Randel, R., Aloise, D., Blanchard, S. J., & Hertz, A. (2021). A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering. Data Mining and Knowledge Discovery, 35(6), 2341-2368. Disponible
