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Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting., , , , , and . CoRR, (2019)Metric Learning from Imbalanced Data., , , and . ICTAI, page 923-930. IEEE, (2019)Metric Learning from Imbalanced Data with Generalization Guarantees., , , and . Pattern Recognit. Lett., (2020)Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting., , , , , , and . ECML/PKDD (3), volume 12459 of Lecture Notes in Computer Science, page 141-157. Springer, (2020)Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport., , and . ECML/PKDD (2), volume 11052 of Lecture Notes in Computer Science, page 759-776. Springer, (2018)MetaAP: A meta-tree-based ranking algorithm optimizing the average precision from imbalanced data., , , and . Pattern Recognit. Lett., (2022)POT: Python Optimal Transport., , , , , , , , , and 12 other author(s). J. Mach. Learn. Res., (2021)Construction de Représentation de Données Adaptées dans le Cadre de Peu d'Exemples Étiquetés. (Learning Tailored Data Representations from Few Labeled Examples).. University of Lyon, France, (2020)