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"

50 / 142 papers shown

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Injectivity of ReLU networks: perspectives from statistical physics Antoine Maillard Afonso S. Bandeira David Belius Ivan Dokmanić S. Nakajima 33 5 0 27 Feb 2023
Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise Teng Fu Yuhao Liu Jean Barbier Marco Mondelli Shansuo Liang Tianqi Hou 19 1 0 07 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width Hugo Cui Florent Krzakala Lenka Zdeborová BDL 27 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 17 0 26 Oct 2022
On double-descent in uncertainty quantification in overparametrized models Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová UQCV 46 12 0 23 Oct 2022
Disordered Systems Insights on Computational Hardness D. Gamarnik Cristopher Moore Lenka Zdeborová AI4CE 38 33 0 15 Oct 2022
Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu Xinshao Wang Jiulong Liu 46 4 0 11 Oct 2022
Bayes-optimal limits in structured PCA, and how to reach them Jean Barbier Francesco Camilli Marco Mondelli Manuel Sáenz 31 5 0 03 Oct 2022
Equivalence of state equations from different methods in High-dimensional Regression Saidi Luo Songtao Tian 13 0 0 25 Sep 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
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? Jean Barbier Tianqi Hou Marco Mondelli Manuel Sáenz 47 14 0 20 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 30 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 26 21 0 22 Mar 2022
The TAP free energy for high-dimensional linear regression Jia Qiu Subhabrata Sen 27 8 0 14 Mar 2022
Bias-variance decomposition of overparameterized regression with random linear features J. Rocks Pankaj Mehta 22 12 0 10 Mar 2022
Theoretical characterization of uncertainty in high-dimensional linear classification Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová 42 20 0 07 Feb 2022
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions Q. Han 29 3 0 20 Jan 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 27 32 0 08 Dec 2021
Towards Designing Optimal Sensing Matrices for Generalized Linear Inverse Problems Junjie Ma Ji Xu A. Maleki 16 3 0 05 Nov 2021
Deep learning via message passing algorithms based on belief propagation C. Lucibello Fabrizio Pittorino Gabriele Perugini R. Zecchina 43 14 0 27 Oct 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
On the Cryptographic Hardness of Learning Single Periodic Neurons M. Song Ilias Zadik Joan Bruna AAML 30 27 0 20 Jun 2021
Nonequilibrium thermodynamics of self-supervised learning D. S. P. Salazar 16 2 0 16 Jun 2021
PCA Initialization for Approximate Message Passing in Rotationally Invariant Models Marco Mondelli R. Venkataramanan 24 19 0 04 Jun 2021
LASSO risk and phase transition under dependence Hanwen Huang 41 3 0 30 Mar 2021
The Geometry of Over-parameterized Regression and Adversarial Perturbations J. Rocks Pankaj Mehta AAML 19 8 0 25 Mar 2021
On the interplay between data structure and loss function in classification problems Stéphane dÁscoli Marylou Gabrié Levent Sagun Giulio Biroli 29 17 0 09 Mar 2021
Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem Francesca Mignacco Pierfrancesco Urbani Lenka Zdeborová 20 34 0 08 Mar 2021
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels Jonathan Niles-Weed Ilias Zadik 18 10 0 24 Feb 2021
Implicit Bias of Linear RNNs M Motavali Emami Mojtaba Sahraee-Ardakan Parthe Pandit S. Rangan A. Fletcher 20 11 0 19 Jan 2021
Solvable Model for Inheriting the Regularization through Knowledge Distillation Luca Saglietti Lenka Zdeborová 12 19 0 01 Dec 2020
Statistical and computational thresholds for the planted $k$ -densest sub-hypergraph problem Luca Corinzia Paolo Penna Wojtek Szpankowski J. M. Buhmann 15 6 0 23 Nov 2020
High-dimensional inference: a statistical mechanics perspective Jean Barbier AI4CE 12 5 0 28 Oct 2020
Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models J. Rocks Pankaj Mehta 23 41 0 26 Oct 2020
Asymptotic Behavior of Adversarial Training in Binary Classification Hossein Taheri Ramtin Pedarsani Christos Thrampoulidis AAML 21 16 0 26 Oct 2020
Approximate Message Passing with Spectral Initialization for Generalized Linear Models Marco Mondelli R. Venkataramanan 20 38 0 07 Oct 2020
Replica Analysis of the Linear Model with Markov or Hidden Markov Signal Priors Lan V. Truong 6 2 0 28 Sep 2020
Strong replica symmetry for high-dimensional disordered log-concave Gibbs measures Jean Barbier D. Panchenko Manuel Sáenz 16 9 0 27 Sep 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 24 133 0 22 Sep 2020
Universality of Linearized Message Passing for Phase Retrieval with Structured Sensing Matrices Rishabh Dudeja Milad Bakhshizadeh 29 12 0 24 Aug 2020
Optimal Combination of Linear and Spectral Estimators for Generalized Linear Models Marco Mondelli Christos Thrampoulidis R. Venkataramanan 13 16 0 07 Aug 2020
The Lasso with general Gaussian designs with applications to hypothesis testing Michael Celentano Andrea Montanari Yuting Wei 42 63 0 27 Jul 2020
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions Stefano Sarao Mannelli Eric Vanden-Eijnden Lenka Zdeborová AI4CE 11 46 0 27 Jun 2020
Information theoretic limits of learning a sparse rule Clément Luneau Jean Barbier N. Macris 20 12 0 19 Jun 2020
Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions Hossein Taheri Ramtin Pedarsani Christos Thrampoulidis 29 28 0 16 Jun 2020
The role of optimization geometry in single neuron learning Nicholas M. Boffi Stephen Tu Jean-Jacques E. Slotine 14 1 0 15 Jun 2020