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Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem


Mar 08, 2021
Francesca Mignacco, Pierfrancesco Urbani, Lenka Zdeborová

* 24 pages, 10 figures 

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Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed


Feb 23, 2021
Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborová

* The accompanying code for this paper is available at https://github.com/mariaref/rfvs2lnn_GMM_online 

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


Feb 16, 2021
Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová

* main: 13 pages, 5 figures; appendix: 52 pages, 4 figures 

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Solvable Model for Inheriting the Regularization through Knowledge Distillation


Dec 02, 2020
Luca Saglietti, Lenka Zdeborová


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Epidemic mitigation by statistical inference from contact tracing data


Sep 20, 2020
Antoine Baker, Indaco Biazzo, Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta, Alessandro Ingrosso, Florent Krzakala, Fabio Mazza, Marc Mézard, Anna Paola Muntoni, Maria Refinetti, Stefano Sarao Mannelli, Lenka Zdeborová

* 21 pages, 7 figures 

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Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions


Jun 27, 2020
Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová

* 10 pages, 4 figures + appendix 

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The Gaussian equivalence of generative models for learning with two-layer neural networks


Jun 25, 2020
Sebastian Goldt, Galen Reeves, Marc Mézard, Florent Krzakala, Lenka Zdeborová

* The accompanying code for this paper is available at https://github.com/sgoldt/gaussian-equiv-2layer 

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Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval


Jun 12, 2020
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová

* 9 pages, 5 figures + appendix 

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Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization


Jun 11, 2020
Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová

* 11 pages + 45 pages Supplementary Material / 5 figures 

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Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification


Jun 10, 2020
Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová

* 8 pages + appendix, 4 figures 

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Phase retrieval in high dimensions: Statistical and computational phase transitions


Jun 09, 2020
Antoine Maillard, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová

* 11 pages (main text and references), 26 pages of supplementary material 

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TRAMP: Compositional Inference with TRee Approximate Message Passing


Apr 03, 2020
Antoine Baker, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová

* Source code available at https://github.com/sphinxteam/tramp. For some examples, see https://github.com/benjaminaubin/tramp_examples 

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The role of regularization in classification of high-dimensional noisy Gaussian mixture


Feb 26, 2020
Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová

* 8 pages + appendix, 6 figures 

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Generalisation error in learning with random features and the hidden manifold model


Feb 21, 2020
Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mézard, Lenka Zdeborová


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Large deviations for the perceptron model and consequences for active learning


Dec 09, 2019
Hugo Cui, Luca Saglietti, Lenka Zdeborová

* 25 pages, 7 figures 

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Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning


Dec 05, 2019
Alia Abbara, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová

* 15 + 10 pages 

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Exact asymptotics for phase retrieval and compressed sensing with random generative priors


Dec 04, 2019
Benjamin Aubin, Bruno Loureiro, Antoine Baker, Florent Krzakala, Lenka Zdeborová

* 12+2 pages, 6 figures 

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Modelling the influence of data structure on learning in neural networks


Sep 25, 2019
Sebastian Goldt, Marc Mézard, Florent Krzakala, Lenka Zdeborová


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Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model


Jul 22, 2019
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová

* 9 pages, 4 figures + appendix 

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Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup


Jun 18, 2019
Sebastian Goldt, Madhu S. Advani, Andrew M. Saxe, Florent Krzakala, Lenka Zdeborová

* 10 pages + references + supplemental material. arXiv admin note: substantial text overlap with arXiv:1901.09085 

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On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix


Jun 11, 2019
Alia Abbara, Antoine Baker, Florent Krzakala, Lenka Zdeborová

* 13 pages, 4 figures 

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The spiked matrix model with generative priors


May 30, 2019
Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová

* 12 + 56, 8 figures, v2 lighter jpeg figures 

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Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model


Feb 01, 2019
Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová

* 12 pages + appendix, 10 figures 

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Generalisation dynamics of online learning in over-parameterised neural networks


Jan 25, 2019
Sebastian Goldt, Madhu S. Advani, Andrew M. Saxe, Florent Krzakala, Lenka Zdeborová

* 25 pages, 13 figures 

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Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference


Dec 21, 2018
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová

* 10 pages and 5 figures + appendix 

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Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method


Dec 06, 2018
Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Lenka Zdeborová

* Submitted to Journal of Machine Learning Research (JMLR) 

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Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models


Nov 01, 2018
Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, Lenka Zdeborová

* 101 pages, 5 figures 

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Entropy and mutual information in models of deep neural networks


Oct 29, 2018
Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová


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Approximate message-passing for convex optimization with non-separable penalties


Sep 17, 2018
Andre Manoel, Florent Krzakala, Gaël Varoquaux, Bertrand Thirion, Lenka Zdeborová

* 18 pages, 6 figures 

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Approximate Survey Propagation for Statistical Inference


Jul 03, 2018
Fabrizio Antenucci, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová

* 37 pages, 14 figures 

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