Ludovic Stephan

According to our database1, Ludovic Stephan authored at least 11 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023
Escaping mediocrity: how two-layer networks learn hard single-index models with SGD.
CoRR, 2023

Learning Two-Layer Neural Networks, One (Giant) Step at a Time.
CoRR, 2023

Universality laws for Gaussian mixtures in generalized linear models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation.
Proceedings of the International Conference on Machine Learning, 2023

From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension.
CoRR, 2022

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sparse random hypergraphs: Non-backtracking spectra and community detection.
Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

2021
A simpler spectral approach for clustering in directed networks.
CoRR, 2021

2019
Robustness of Spectral Methods for Community Detection.
Proceedings of the Conference on Learning Theory, 2019

Planting trees in graphs, and finding them back.
Proceedings of the Conference on Learning Theory, 2019


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