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ORCIDLudovic Stephan
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2020 – today
- 2024
[c9]Ludovic Stephan, Yizhe Zhu:
A non-backtracking method for long matrix and tensor completion. COLT 2024: 4636-4690- [c8]Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan:
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs. ICML 2024 - [i10]Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Luca Pesce
, Ludovic Stephan:
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions. CoRR abs/2405.15459 (2024) - [i9]Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan:
Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs. CoRR abs/2406.02157 (2024) - 2023
- [c7]Luca Arnaboldi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro:
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks. COLT 2023: 1199-1227 - [c6]Luca Pesce, Florent Krzakala, Bruno Loureiro, Ludovic Stephan:
Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation. ICML 2023: 27680-27708 - [c5]Yatin Dandi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro, Lenka Zdeborová:
Universality laws for Gaussian mixtures in generalized linear models. NeurIPS 2023 - [i8]Luca Arnaboldi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro:
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks. CoRR abs/2302.05882 (2023) - [i7]Luca Pesce, Florent Krzakala, Bruno Loureiro, Ludovic Stephan:
Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimation. CoRR abs/2302.08923 (2023) - [i6]Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan:
Learning Two-Layer Neural Networks, One (Giant) Step at a Time. CoRR abs/2305.18270 (2023) - [i5]Luca Arnaboldi, Florent Krzakala, Bruno Loureiro, Ludovic Stephan:
Escaping mediocrity: how two-layer networks learn hard single-index models with SGD. CoRR abs/2305.18502 (2023) - 2022
- [c4]Ludovic Stephan, Yizhe Zhu:
Sparse random hypergraphs: Non-backtracking spectra and community detection. FOCS 2022: 567-575 - [c3]Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová:
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. NeurIPS 2022 - [i4]Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová:
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. CoRR abs/2202.00293 (2022) - [i3]Federica Gerace, Florent Krzakala, Bruno Loureiro, Ludovic Stephan, Lenka Zdeborová:
Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension. CoRR abs/2205.13303 (2022) - 2021
- [i2]Simon Coste, Ludovic Stephan:
A simpler spectral approach for clustering in directed networks. CoRR abs/2102.03188 (2021)
2010 – 2019
- 2019
- [c2]Laurent Massoulié, Ludovic Stephan, Don Towsley:
Planting trees in graphs, and finding them back. COLT 2019: 2341-2371 - [c1]Ludovic Stephan, Laurent Massoulié:
Robustness of Spectral Methods for Community Detection. COLT 2019: 2831-2860 - 2018
- [i1]Ludovic Stephan, Laurent Massoulié:
Robustness of spectral methods for community detection. CoRR abs/1811.05808 (2018)
Coauthor Index
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