Cédric Gerbelot

According to our database, Cédric Gerbelot authored at least 16 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods.

Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco, Florent Krzakala, Lenka Zdeborová

SIAM J. Math. Data Sci., 2024

Permutation recovery of spikes in noisy high-dimensional tensor estimation.

Gérard Ben Arous, Cédric Gerbelot, Vanessa Piccolo

CoRR, 2024

Stochastic gradient descent in high dimensions for multi-spiked tensor PCA.

Gérard Ben Arous, Cédric Gerbelot, Vanessa Piccolo

CoRR, 2024

High-dimensional optimization for multi-spiked tensor PCA.

Gérard Ben Arous, Cédric Gerbelot, Vanessa Piccolo

CoRR, 2024

2023

Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima's Replica Formula).

Cédric Gerbelot, Alia Abbara, Florent Krzakala

IEEE Trans. Inf. Theory, March, 2023

Learning curves for the multi-class teacher-student perceptron.

Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, Cédric Gerbelot, Bruno Loureiro, Lenka Zdeborová

Mach. Learn. Sci. Technol., March, 2023

Applying statistical learning theory to deep learning.

Cédric Gerbelot, Avetik Karagulyan, Stefani Karp, Kavya Ravichandran, Menachem Stern, Nathan Srebro

CoRR, 2023

2022

Statistical learning in high dimensions: a rigorous statistical physics approach. (Apprentissage statistique en grandes dimensions: une approche rigoureuse par la physique statistique).

Cédric Gerbelot

PhD thesis, 2022

Multi-layer State Evolution Under Random Convolutional Design.

Max Daniels, Cédric Gerbelot, Florent Krzakala, Lenka Zdeborová

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension.

Bruno Loureiro, Cédric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala

Proceedings of the International Conference on Machine Learning, 2022

2021

Graph-based Approximate Message Passing Iterations.

Cédric Gerbelot, Raphaël Berthier

CoRR, 2021

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

Bruno Loureiro, Gabriele Sicuro, Cédric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborová

CoRR, 2021

Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model.

Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová

CoRR, 2021

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

Bruno Loureiro, Gabriele Sicuro, Cédric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborová

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning curves of generic features maps for realistic datasets with a teacher-student model.

Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices.

Cédric Gerbelot, Alia Abbara, Florent Krzakala

Proceedings of the Conference on Learning Theory, 2020