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Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions.

, , , , , and . NeurIPS, page 10144-10157. (2021)

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Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima's Replica Formula)., , and . IEEE Trans. Inf. Theory, 69 (3): 1824-1852 (March 2023)Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions., , , , , and . CoRR, (2021)Learning curves for the multi-class teacher-student perceptron., , , , , and . Mach. Learn. Sci. Technol., 4 (1): 15019 (March 2023)Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima's Replica Formula)., , and . CoRR, (2020)Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model., , , , , , and . CoRR, (2021)Learning curves of generic features maps for realistic datasets with a teacher-student model., , , , , , and . NeurIPS, page 18137-18151. (2021)Applying statistical learning theory to deep learning., , , , , and . CoRR, (2023)Statistical learning in high dimensions: a rigorous statistical physics approach. (Apprentissage statistique en grandes dimensions: une approche rigoureuse par la physique statistique).. PSL University, Paris, France, (2022)Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions., , , , , and . NeurIPS, page 10144-10157. (2021)Learning curves for the multi-class teacher-student perceptron., , , , , and . CoRR, (2022)