( en | de | ru )

 

Disambiguation of "Gerbelot, Cédric"

Author of the publication

copydeleteadd this publication to your clipboard
Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices.

, , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 1682-1713. PMLR, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Cédric Bodet

Cédric Müller

Cédric Allène

Cédric Joffroy

Cédric Penet

 

Other publications of authors with the same name

Learning curves of generic features maps for realistic datasets with a teacher-student model., , , , , , and . NeurIPS, page 18137-18151. (2021)Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions., , , , , and . CoRR, (2021)Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension., , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 14283-14314. PMLR, (2022)Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices., , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 1682-1713. PMLR, (2020)Multi-layer State Evolution Under Random Convolutional Design., , , and . NeurIPS, (2022)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)Applying statistical learning theory to deep learning., , , , , and . CoRR, (2023)Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions., , , , , and . NeurIPS, page 10144-10157. (2021)High-dimensional optimization for multi-spiked tensor PCA., , and . CoRR, (2024)Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods., , , , and . SIAM J. Math. Data Sci., 6 (2): 400-427 (2024)