Publications

Statistical mechanics of the maximum-average submatrix problem

V. Erba; F. Krzakala; R. Perez Ortiz; L. Zdeborova

Journal Of Statistical Mechanics-Theory And Experiment

2024-01-01

Vol. 2024 , num. 1, p. 013403.

DOI : 10.1088/1742-5468/ad1391

2023

Fluctuations, bias, variance and ensemble of learners: exact asymptotics for convex losses in high-dimension

B. Loureiro; C. Gerbelot; M. Refinetti; G. Sicuro; F. Krzakala

Journal Of Statistical Mechanics-Theory And Experiment

2023-11-01

Vol. 2023 , num. 11, p. 114001.

DOI : 10.1088/1742-5468/ad0221

Phase diagram of stochastic gradient descent in high-dimensional two-layer neural networks

R. Veiga; L. Stephan; B. Loureiro; F. Krzakala; L. Zdeborova

Journal Of Statistical Mechanics-Theory And Experiment

2023-11-01

Vol. 2023 , num. 11, p. 114008.

DOI : 10.1088/1742-5468/ad01b1

Multi-layer state evolution under random convolutional design

M. Daniels; C. Gerbelot; F. Krzakala; L. Zdeborova

Journal Of Statistical Mechanics-Theory And Experiment

2023-11-01

Vol. 2023 , num. 11, p. 114002.

DOI : 10.1088/1742-5468/ad0220

Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment

K. Müller; J. Launay; I. Poli; M. Filipovich; A. Capelli et al.

2023 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC)

2023

2023 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), Munich, Germany, June 26-30, 2023 .

p. 1-1

DOI : 10.1109/CLEO/Europe-EQEC57999.2023.10231380

Error scaling laws for kernel classification under source and capacity conditions

H. C. Cui; B. Loureiro; F. Krzakala; L. Zdeborová

IOPscience

2023

num. Mach. Learn.: Sci. Technol. 4 035033.

DOI : 10.1088/2632-2153/acf041

Bayes-optimal Learning of Deep Random Networks of Extensive-width

H. C. Cui; F. Krzakala; L. Zdeborová

Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023

2023

International Conference on Machine Learning, Honolulu, Hawaii, USA, July 23-29, 2023.

Expectation consistency for calibration of neural networks

L. A. Clarte; B. Loureiro; F. Krzakala; L. Zdeborová

Uncertainty in Artificial Intelligence

2023

Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI 2023), PMLR 216:443–453., Pittsburgh, PA, USA, August 31-4, 2023.

Compressed sensing with ℓ 0-norm: statistical physics analysis & algorithms for signal recovery

D. Barbier; C. Lucibello; L. Saglietti; F. Krzakala; L. Zdeborova

2023 Ieee Information Theory Workshop, Itw

2023-01-01

IEEE Information Theory Workshop (ITW), Saint-Malo, FRANCE, Apr 23-28, 2023.

p. 323-328

DOI : 10.1109/ITW55543.2023.10161684

Theoretical characterization of uncertainty in high-dimensional linear classification

L. Clarte; B. Loureiro; F. Krzakala; L. Zdeborova

Machine Learning-Science And Technology

2023-06-01

Vol. 4 , num. 2, p. 025029.

DOI : 10.1088/2632-2153/acd749

On double-descent in uncertainty quantification in overparametrized models

L. A. Clarte; B. Loureiro; F. Krzakala; L. Zdeborová

Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS)

2023

26th International Conference on Artificial Intelligence and Statistics (AISTATS) , Palau de Congressos, Valencia, Spain, April 25-27, 2023.

p. 7089-7125

Tree-AMP: Compositional Inference with Tree Approximate Message Passing

A. Baker; B. Aubin; F. Krzakala; L. Zdeborová

Journal of Machine Learning Research

2023

Vol. 24 , num. 57, p. 1–89.

Bayesian reconstruction of memories stored in neural networks from their connectivity

S. Goldt; F. Krzakala; L. Zdeborová; N. Brunel

PLoS Comput Biol

2023-01-30

Vol. 19 , p. e1010813.

DOI : 10.1371/journal.pcbi.1010813

2022

Multi-layer State Evolution Under Random Convolutional Design

M. Daniels; C. Gerbelot; F. Krzakala; L. Zdeborová

NeurIPS Proceedings

2022

Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap

L. Pesce; B. Loureiro; F. Krzakala; L. Zdeborová

2022

36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans , November 28-December 9, 2022.

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

R. Veiga; L. Stephan; B. Loureiro; F. Krzakala; L. Zdeborová

2022

36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, November 28-December 9, 2022.

Optimal denoising of rotationally invariant rectangular matrices

E. Troiani; V. Erba; F. Krzakala; A. Maillard; L. Zdeborová

Proceedings of Mathematical and Scientific Machine Learning

2022

Vol. 190 , p. 97-112.

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

B. Loureiro; C. Gerbelot; M. Refinetti; G. Sicuro; F. Krzakala

International Conference On Machine Learning, Vol 162

2022-01-01

38th International Conference on Machine Learning (ICML), Baltimore, MD, Jul 17-23, 2022.

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

C. Gerbelot; A. Abbara; F. Krzakala

IEEE Transactions on Information Theory

2022-11-17

Vol. 69 , num. 3, p. 1824-1852.

DOI : 10.1109/TIT.2022.3222913

Generalization error rates in kernel regression: the crossover from the noiseless to noisy regime*

H. Cui; B. Loureiro; F. Krzakala; L. Zdeborova

Journal Of Statistical Mechanics-Theory And Experiment

2022-11-01

Vol. 2022 , num. 11, p. 114004.

DOI : 10.1088/1742-5468/ac9829

Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients

A. Cappelli; R. Ohana; J. Launay; L. Meunier; I. Poli et al.

ICASSP 2022 – 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

2022-04-27

ICASSP 2022 – 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, May 23-27, 2022.

p. 3493-3497

DOI : 10.1109/ICASSP43922.2022.9746671

Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising

A. Maillard; F. Krzakala; M. Mézard; L. Zdeborová

Journal of Statistical Mechanics: Theory and Experiment

2022-08-10

Vol. 2022 , num. 8, p. 083301.

DOI : 10.1088/1742-5468/ac7e4c

2021

The Gaussian equivalence of generative models for learning with shallow neural networks

S. Goldt; B. Loureiro; G. Reeves; F. Krzakala; M. Mezard et al.

Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference

2021-12-16

2nd Mathematical and Scientific Machine Learning Conference, Online, August 16-19, 2021.

Construction of optimal spectral methods in phase retrieval

A. Maillard; F. Krzakala; l. Yue; L. Zdeborová

Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference

2021-08-16

2nd Conference on Mathematical and Scientific Machine Learning (MSML 2021), Lausanne, Suisse, August 16-19, 2021.

p. 693-720

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

B. Loureiro; G. Sicuro; C. Gerbelot; A. Pacco; F. Krzakala et al.

Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021)

2021

35th Conference on Neural Information Processing Systems (NeurIPS 2021), Online, December 7-10, 2021.

Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime

H. C. Cui; B. Loureiro; F. Krzakala; L. Zdeborová

Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021)

2021

35th Conference on Neural Information Processing Systems (NeurIPS 2021), Online, December 7-10, 2021.

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

B. Loureiro; C. Gerbelot; H. C. Cui; S. Goldt; F. Krzakala et al.

Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021)

2021

35th Conference on Neural Information Processing Systems (NeurIPS 2021), Online, December 7-10, 2021.

p. 16-58

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

F. Mignacco; F. Krzakala; P. Urbani; A. L. Zdeborova

Journal Of Statistical Mechanics-Theory And Experiment

2021-12-01

Vol. 2021 , num. 12, p. 124008.

DOI : 10.1088/1742-5468/ac3a80

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

F. Gerace; B. Loureiro; F. Krzakala; M. Mezard; L. Zdeborova

Journal Of Statistical Mechanics-Theory And Experiment

2021-12-01

Vol. 2021 , num. 12, p. 124013.

DOI : 10.1088/1742-5468/ac3ae6

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

M. Refinetti; S. Goldt; F. Krzakala; L. Zdeborová

Proceedings of the 38th International Conference on Machine Learning

2021-07-21

38th International Conference on Machine Learning (ICML), Virtual, July 18-24, 2021.

p. 8936-8947

Epidemic mitigation by statistical inference from contact tracing data

A. Baker; I. Biazzo; A. Braunstein; G. Catania; L. Dall’Asta et al.

Proceedings Of The National Academy Of Sciences Of The United States Of America

2021-08-10

Vol. 118 , num. 32, p. e2106548118.

DOI : 10.1073/pnas.2106548118

2020

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

B. Aubin; F. Krzakala; L. Yue; L. Zdeborová

Proceeding of the 2020 Advances in Neural Information Processing Systems

2020

Advances in Neural Information Processing Systems, Dec 6, 2020 – Dec 12, 2020.

p. 12199–12210

Phase retrieval in high dimensions: Statistical and computational phase transitions

A. Maillard; B. Loureiro; F. Krzakala; L. Zdeborová

Proceeding of the 2020 Advances in Neural Information Processing Systems

2020

Advances in Neural Information Processing Systems, Dec 6, 2020 – Dec 12, 2020.

p. 11071–11082

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

F. Mignacco; F. Krzakala; P. Urbani; L. Zdeborová

Proceeding of the 2020 Advances in Neural Information Processing Systems

2020

Advances in Neural Information Processing Systems, Dec 6, 2020 – Dec 12, 2020.

p. 9540–955

Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures

J. Launay; I. Poli; F. Boniface; F. Krzakala

Proceeding of the 2020 Advances in Neural Information Processing Systems

2020

Advances in Neural Information Processing Systems, Dec 6, 2020 – Dec 12, 2020.

p. 9346–9360

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

S. Sarao Mannelli; G. Biroli; C. Cammarota; F. Krzakala; P. Urbani et al.

Proceeding of the 2020 Advances in Neural Information Processing Systems

2020

Advances in Neural Information Processing Systems, Dec 6, 2020 – Dec 12, 2020.

p. 3265–3274

Reservoir Computing meets Recurrent Kernels and Structured Transforms

J. Dong; R. Ohana; M. Rafayelyan; f. Krzakala

Proceeding of the 2020 Advances in Neural Information Processing Systems

2020

Advances in Neural Information Processing Systems, Dec 6, 2020 – Dec 12, 2020.

p. 16785–16796

The Spiked Matrix Model With Generative Priors

B. Aubin; B. Loureiro; A. Maillard; F. Krzakala; L. Zdeborova

IEEE Transactions on Information Theory

2020-10-27

Vol. 67 , num. 2, p. 1156-1181.

DOI : 10.1109/TIT.2020.3033985

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

J. Barbier; N. Macris; M. Dia; F. Krzakala

Ieee Transactions On Information Theory

2020-07-01

Vol. 66 , num. 7, p. 4270-4303.

DOI : 10.1109/TIT.2020.2990880

2019

Entropy and mutual information in models of deep neural networks

M. Gabrie; A. Manoel; C. Luneau; J. Barbier; N. Macris et al.

Journal Of Statistical Mechanics-Theory And Experiment

2019-12-01

Vol. 2019 , num. 12, p. 124014.

DOI : 10.1088/1742-5468/ab3430

The committee machine: computational to statistical gaps in learning a two-layers neural network

B. Aubin; A. Maillard; J. Barbier; F. Krzakala; N. Macris et al.

Journal Of Statistical Mechanics-Theory And Experiment

2019-12-01

Vol. 2019 , num. 12, p. 124023.

DOI : 10.1088/1742-5468/ab43d2

Optimal errors and phase transitions in high-dimensional generalized linear models

J. Barbier; F. Krzakala; N. Macris; L. Miolane; L. Zdeborova

Proceedings of the National Academy of Sciences

2019-03-19

Vol. 116 , num. 12, p. 5451-5460.

DOI : 10.1073/pnas.1802705116

2018

Entropy and mutual information in models of deep neural networks

M. Gabrie; A. Manoel; C. Luneau; J. Barbier; N. Macris et al.

Advances In Neural Information Processing Systems 31 (Nips 2018)

2018-01-01

32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.

The committee machine: Computational to statistical gaps in learning a two-layers neural network

B. Aubin; A. Maillard; J. Barbier; F. Krzakala; N. Macris et al.

Advances In Neural Information Processing Systems 31 (Nips 2018)

2018-01-01

32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

J. Barbier; N. Macris; A. Maillard; F. Krzakala

2018 Ieee International Symposium On Information Theory (Isit)

2018-01-01

IEEE International Symposium on Information Theory (ISIT), Vail, CO, Jun 17-22, 2018.

p. 1390-1394

DOI : 10.1109/ISIT.2018.8437522

2016

Scampi: a robust approximate message-passing framework for compressive imaging

J. Barbier; E. W. Tramel; F. Krzakala

International Meeting On High-Dimensional Data-Driven Science (Hd3-2015)

2016

International Meeting on High-Dimensional Data-Driven Science (HD3), Kyoto, JAPAN, DEC 14-17, 2015.

p. 012013

DOI : 10.1088/1742-6596/699/1/012013