Ludovic Stephan

23 papers A* 10Journal 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
Wedge Sampling: Efficient Tensor Completion with Nearly-Linear Sample Complexity.
CoRR
Hengrui Luo, Anna Ma, Ludovic Stephan, Yizhe Zhu
2025 J jnl
Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks.
CoRR
Luca Arnaboldi, Bruno Loureiro, Ludovic Stephan, Florent Krzakala, Lenka Zdeborová
2025 A* conf
Community detection with the Bethe-Hessian.
COLT
Ludovic Stephan, Yizhe Zhu
2024 A* conf
A non-backtracking method for long matrix and tensor completion.
COLT
Ludovic Stephan, Yizhe Zhu
2024 J jnl
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time.
J. Mach. Learn. Res.
Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2024 J jnl
Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs.
CoRR
Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2024 A* conf
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs.
ICML
Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2024 J jnl
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions.
CoRR
Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Luca Pesce, Ludovic Stephan
2023 A* conf
Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation.
ICML
Luca Pesce, Florent Krzakala, Bruno Loureiro, Ludovic Stephan
2023 J jnl
Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimation.
CoRR
Luca Pesce, Florent Krzakala, Bruno Loureiro, Ludovic Stephan
2023 J jnl
Escaping mediocrity: how two-layer networks learn hard single-index models with SGD.
CoRR
Luca Arnaboldi, Florent Krzakala, Bruno Loureiro, Ludovic Stephan
2023 A* conf
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks.
COLT
Luca Arnaboldi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro
2023 J jnl
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks.
CoRR
Luca Arnaboldi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro
2023 J jnl
Learning Two-Layer Neural Networks, One (Giant) Step at a Time.
CoRR
Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2023 A* conf
Universality laws for Gaussian mixtures in generalized linear models.
NeurIPS
Yatin Dandi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro, Lenka Zdeborová
2022 J jnl
Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension.
CoRR
Federica Gerace, Florent Krzakala, Bruno Loureiro, Ludovic Stephan, Lenka Zdeborová
2022 A* conf
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks.
NeurIPS
Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022 J jnl
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks.
CoRR
Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022 A* conf
Sparse random hypergraphs: Non-backtracking spectra and community detection.
FOCS
Ludovic Stephan, Yizhe Zhu
2021 J jnl
A simpler spectral approach for clustering in directed networks.
CoRR
Simon Coste, Ludovic Stephan
2019 A* conf
Planting trees in graphs, and finding them back.
COLT
Laurent Massoulié, Ludovic Stephan, Don Towsley
2019 A* conf
Robustness of Spectral Methods for Community Detection.
COLT
Ludovic Stephan, Laurent Massoulié
2018 J jnl
Robustness of spectral methods for community detection.
CoRR
Ludovic Stephan, Laurent Massoulié