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Pallage, J. (2025). Contributions to the Trustworthy Machine Learning Pipeline: Data Selection, Training, and Post-training Verification through Convexity and the Wasserstein Distance [Mémoire de maîtrise, Polytechnique Montréal]. Disponible
Pallage, J., & Lesage-Landry, A. (décembre 2025). Sliced-Wasserstein Distance-based Data Selection [Communication écrite]. International Conference on Machine Learning and Applications (ICMLA 2025), Boca Raton, FL, USA. Lien externe
Pallage, J., & Lesage-Landry, A. (2025). Wasserstein Distributionally Robust Shallow Convex Neural Networks. INFORMS Journal on Optimization. Lien externe
