p-Sparsified Sketches for Fast Multiple Output Kernel Methods. - Tamim El Ahmad; Pierre Laforgue; Florence d'Alché-Buc (CoRR, 2022)

Fast Kernel Methods for Generic Lipschitz Losses via p-Sparsified Sketches. - Tamim El Ahmad; Pierre Laforgue; Florence d'Alché-Buc (Trans. Mach. Learn. Res., 2023)

Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels. - Tamim El Ahmad; Luc Brogat-Motte; Pierre Laforgue; Florence d'Alché-Buc (AISTATS, 2024)

Deep Sketched Output Kernel Regression for Structured Prediction. - Tamim El Ahmad; Junjie Yang; Pierre Laforgue; Florence d'Alché-Buc (ECML/PKDD (3), 2024)

Learning deep kernel networks : application to efficient and robust structured prediction. (Apprentissage de réseaux profonds à noyaux pour la prédiction structurée efficace et robuste). - Tamim El Ahmad (2024)