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

10 August 2017

Lenka Zdeborová

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

48 / 48 papers shown

Title
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime Francesco Camilli D. Tieplova Eleonora Bergamin Jean Barbier 120 0 0 06 May 2025
The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model Kaito Takanami Takashi Takahashi Ayaka Sakata 40 0 0 27 Jan 2025
On the phase diagram of extensive-rank symmetric matrix denoising beyond rotational invariance Jean Barbier Francesco Camilli Justin Ko Koki Okajima 34 5 0 04 Nov 2024
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics Alireza Mousavi-Hosseini Denny Wu Murat A. Erdogdu MLT AI4CE 35 6 0 14 Aug 2024
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions Luca Arnaboldi Yatin Dandi Florent Krzakala Luca Pesce Ludovic Stephan 70 12 0 24 May 2024
Inferring the Graph of Networked Dynamical Systems under Partial Observability and Spatially Colored Noise Augusto Santos Diogo Rente Rui Seabra José M. F. Moura 16 1 0 18 Dec 2023
Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise Augusto Santos Diogo Rente Rui Seabra José M. F. Moura 16 4 0 10 Dec 2023
Fitting an ellipsoid to random points: predictions using the replica method Antoine Maillard Dmitriy Kunisky 28 2 0 02 Oct 2023
Gibbs Sampling the Posterior of Neural Networks Giovanni Piccioli Emanuele Troiani Lenka Zdeborová 41 2 0 05 Jun 2023
Moment-Based Adjustments of Statistical Inference in High-Dimensional Generalized Linear Models Kazuma Sawaya Yoshimasa Uematsu Masaaki Imaizumi 31 2 0 28 May 2023
Neural-prior stochastic block model O. Duranthon L. Zdeborová 41 3 0 17 Mar 2023
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture Minh-Toan Nguyen Romain Couillet 27 4 0 03 Mar 2023
Sharp thresholds in inference of planted subgraphs Elchanan Mossel Jonathan Niles-Weed Youngtak Sohn Nike Sun Ilias Zadik 10 6 0 28 Feb 2023
Injectivity of ReLU networks: perspectives from statistical physics Antoine Maillard Afonso S. Bandeira David Belius Ivan Dokmanić S. Nakajima 28 5 0 27 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width Hugo Cui Florent Krzakala Lenka Zdeborová BDL 20 35 0 01 Feb 2023
Near-optimal multiple testing in Bayesian linear models with finite-sample FDR control Taejoon Ahn Licong Lin Song Mei 24 3 0 04 Nov 2022
Grokking phase transitions in learning local rules with gradient descent Bojan Žunkovič E. Ilievski 63 16 0 26 Oct 2022
Disordered Systems Insights on Computational Hardness D. Gamarnik Cristopher Moore Lenka Zdeborová AI4CE 35 33 0 15 Oct 2022
Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu Xinshao Wang Jiulong Liu 43 4 0 11 Oct 2022
Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap Luca Pesce Bruno Loureiro Florent Krzakala Lenka Zdeborová 38 1 0 26 May 2022
Fundamental limits to learning closed-form mathematical models from data Oscar Fajardo-Fontiveros I. Reichardt Harry R. De Los Ríos Jordi Duch M. Sales-Pardo R. Guimerà 22 19 0 06 Apr 2022
Learning curves for the multi-class teacher-student perceptron Elisabetta Cornacchia Francesca Mignacco R. Veiga Cédric Gerbelot Bruno Loureiro Lenka Zdeborová 23 21 0 22 Mar 2022
The TAP free energy for high-dimensional linear regression Jia Qiu Subhabrata Sen 25 8 0 14 Mar 2022
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning Ali Bereyhi Bruno Loureiro Florent Krzakala R. Muller H. Schulz-Baldes 35 2 0 19 Jan 2022
Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing R. Venkataramanan Kevin Kögler Marco Mondelli 24 32 0 08 Dec 2021
Approximate Message Passing for orthogonally invariant ensembles: Multivariate non-linearities and spectral initialization Xinyi Zhong Tianhao Wang Zhou-Yang Fan 29 20 0 05 Oct 2021
Performance of Bayesian linear regression in a model with mismatch Jean Barbier Wei-Kuo Chen D. Panchenko Manuel Sáenz 40 22 0 14 Jul 2021
Instance-Optimal Compressed Sensing via Posterior Sampling A. Jalal Sushrut Karmalkar A. Dimakis Eric Price 26 51 0 21 Jun 2021
LASSO risk and phase transition under dependence Hanwen Huang 41 3 0 30 Mar 2021
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels Jonathan Niles-Weed Ilias Zadik 15 10 0 24 Feb 2021
Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models J. Rocks Pankaj Mehta 18 41 0 26 Oct 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 22 133 0 22 Sep 2020
The Lasso with general Gaussian designs with applications to hypothesis testing Michael Celentano Andrea Montanari Yuting Wei 42 63 0 27 Jul 2020
Phase retrieval in high dimensions: Statistical and computational phase transitions Antoine Maillard Bruno Loureiro Florent Krzakala Lenka Zdeborová 23 57 0 09 Jun 2020
Information-Theoretic Limits for the Matrix Tensor Product Galen Reeves 30 29 0 22 May 2020
Reducibility and Statistical-Computational Gaps from Secret Leakage Matthew Brennan Guy Bresler 29 86 0 16 May 2020
The estimation error of general first order methods Michael Celentano Andrea Montanari Yuchen Wu 14 44 0 28 Feb 2020
Generalisation error in learning with random features and the hidden manifold model Federica Gerace Bruno Loureiro Florent Krzakala M. Mézard Lenka Zdeborová 25 165 0 21 Feb 2020
Asymptotic errors for convex penalized linear regression beyond Gaussian matrices Cédric Gerbelot A. Abbara Florent Krzakala 34 16 0 11 Feb 2020
Inference in Multi-Layer Networks with Matrix-Valued Unknowns Parthe Pandit Mojtaba Sahraee-Ardakan S. Rangan P. Schniter A. Fletcher 23 6 0 26 Jan 2020
Thresholds of descending algorithms in inference problems Stefano Sarao Mannelli Lenka Zdeborova AI4CE 24 4 0 02 Jan 2020
Modelling the influence of data structure on learning in neural networks: the hidden manifold model Sebastian Goldt M. Mézard Florent Krzakala Lenka Zdeborová BDL 26 51 0 25 Sep 2019
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting Marc Lelarge Léo Miolane 14 28 0 08 Jul 2019
Understanding Phase Transitions via Mutual Information and MMSE Galen Reeves H. Pfister 11 7 0 03 Jul 2019
Fundamental Barriers to High-Dimensional Regression with Convex Penalties Michael Celentano Andrea Montanari 33 46 0 25 Mar 2019
The committee machine: Computational to statistical gaps in learning a two-layers neural network Benjamin Aubin Antoine Maillard Jean Barbier Florent Krzakala N. Macris Lenka Zdeborová 41 104 0 14 Jun 2018
Entropy and mutual information in models of deep neural networks Marylou Gabrié Andre Manoel Clément Luneau Jean Barbier N. Macris Florent Krzakala Lenka Zdeborová 30 178 0 24 May 2018
A New Approach to Laplacian Solvers and Flow Problems Patrick Rebeschini S. Tatikonda 19 8 0 22 Nov 2016