Bruno Loureiro

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 56

Top Topics

High Dimensions

Generalized Linear

Learning Curves

Top Venues

IEEE Trans. Inf. Theory

Publications

Dominik Schröder, Daniil Dmitriev, Hugo Cui, Bruno Loureiro
Asymptotics of Learning with Deep Structured (Random) Features. CoRR (2024)
Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro
Asymptotics of feature learning in two-layer networks after one gradient-step. CoRR (2024)
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 (2024)
Lucas Clarté, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression. CoRR (2024)
Leonardo Defilippis, Bruno Loureiro, Theodor Misiakiewicz
Dimension-free deterministic equivalents for random feature regression. CoRR (2024)
Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro, Florent Krzakala
A High Dimensional Model for Adversarial Training: Geometry and Trade-Offs. CoRR (2024)
Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborová, Bruno Loureiro, Florent Krzakala
Fundamental limits of weak learnability in high-dimensional multi-index models. CoRR (2024)
Dominik Schröder, Hugo Cui, Daniil Dmitriev, Bruno Loureiro
Deterministic equivalent and error universality of deep random features learning. ICML (2023)
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 (2023)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
On double-descent in uncertainty quantification in overparametrized models. AISTATS (2023)
Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Error scaling laws for kernel classification under source and capacity conditions. Mach. Learn. Sci. Technol. 4 (3) (2023)
Urte Adomaityte, Leonardo Defilippis, Bruno Loureiro, Gabriele Sicuro
High-dimensional robust regression under heavy-tailed data: Asymptotics and Universality. CoRR (2023)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Expectation consistency for calibration of neural networks. UAI (2023)
Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
Bayesian Inference With Nonlinear Generative Models: Comments on Secure Learning. IEEE Trans. Inf. Theory 69 (12) (2023)
Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
Learning Two-Layer Neural Networks, One (Giant) Step at a Time. CoRR (2023)
Luca Arnaboldi, Florent Krzakala, Bruno Loureiro, Ludovic Stephan
Escaping mediocrity: how two-layer networks learn hard single-index models with SGD. CoRR (2023)
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)
Yatin Dandi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro, Lenka Zdeborová
Universality laws for Gaussian mixtures in generalized linear models. NeurIPS (2023)
Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, Cédric Gerbelot, Bruno Loureiro, Lenka Zdeborová
Learning curves for the multi-class teacher-student perceptron. Mach. Learn. Sci. Technol. 4 (1) (2023)
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)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Expectation consistency for calibration of neural networks. CoRR (2023)
Dominik Schröder, Hugo Cui, Daniil Dmitriev, Bruno Loureiro
Deterministic equivalent and error universality of deep random features learning. CoRR (2023)
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 (2023)
Bruno Loureiro, Cédric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension. CoRR (2022)
Federica Gerace, Florent Krzakala, Bruno Loureiro, Ludovic Stephan, Lenka Zdeborová
Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension. CoRR (2022)
Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Error Rates for Kernel Classification under Source and Capacity Conditions. CoRR (2022)
Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
Secure Coding via Gaussian Random Fields. CoRR (2022)
Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap. NeurIPS (2022)
Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Subspace clustering in high-dimensions: Phase transitions \& Statistical-to-Computational gap. CoRR (2022)
Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
Secure Coding via Gaussian Random Fields. ISIT (2022)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
A study of uncertainty quantification in overparametrized high-dimensional models. CoRR (2022)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Theoretical characterization of uncertainty in high-dimensional linear classification. CoRR (2022)
José Pinto, Maria Costa, Renato Mendes, Keila Lima, Paulo Sousa Dias, João Pereira, Manuel A. Ribeiro, Renato Campos, Maria Paola Tomasino, Catarina Magalhães, Francisco López Castejón, Javier Gilabert, Adriana M. Santos-Ferreira, José C. B. da Silva, Paulo Relvas, Trent Lukaczyk, Kay Arne Skarpnes, Emlyn J. Davies, Alexander Chekalyuk, Bruno Loureiro, Ian G. Brosnan, Jing Li, João Borges de Sousa, Kanna Rajan
Coordinated Robotic Exploration of Dynamic Open Ocean Phenomena. Field Robotics 2 (1) (2022)
Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, Cédric Gerbelot, Bruno Loureiro, Lenka Zdeborová
Learning curves for the multi-class teacher-student perceptron. CoRR (2022)
Bruno Loureiro, Cédric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension. ICML (2022)
Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. CoRR (2022)
Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning. CoRR (2022)
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)
Sebastian Goldt, Bruno Loureiro, Galen Reeves, Florent Krzakala, Marc Mézard, Lenka Zdeborová
The Gaussian equivalence of generative models for learning with shallow neural networks. MSML (2021)
Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová
Learning curves of generic features maps for realistic datasets with a teacher-student model. NeurIPS (2021)
Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. NeurIPS (2021)
Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová
The Spiked Matrix Model With Generative Priors. IEEE Trans. Inf. Theory 67 (2) (2021)
Bruno Loureiro, Gabriele Sicuro, Cédric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborová
Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions. NeurIPS (2021)
Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. CoRR (2021)
Bruno Loureiro, Gabriele Sicuro, Cédric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborová
Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions. CoRR (2021)
Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová
Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model. CoRR (2021)
Benjamin Aubin, Bruno Loureiro, Antoine Baker, Florent Krzakala, Lenka Zdeborová
Exact asymptotics for phase retrieval and compressed sensing with random generative priors. MSML (2020)
José Pinto, Maria Costa, Keila Lima, Paulo Sousa Dias, João Pereira, Manuel A. Ribeiro, Renato Campos, Zara Mirmalek, Renato Mendes, Francisco López Castejón, Javier Gilabert, Maria Paola Tomasino, Catarina Magalhães, José C. B. da Silva, Paulo Relvas, Trent Lukaczyk, Kay Arne Skarpnes, Martin Ludvigsen, Alexander Chekalyuk, Bruno Loureiro, Ian G. Brosnan, Jing Li, Ami Hannon, João Borges de Sousa, Kanna Rajan
To Boldly Dive Where No One Has Gone Before: Experiments in Coordinated Robotic Ocean Exploration. ISER (2020)
Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mézard, Lenka Zdeborová
Generalisation error in learning with random features and the hidden manifold model. ICML (2020)
Antoine Maillard, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Phase retrieval in high dimensions: Statistical and computational phase transitions. NeurIPS (2020)
Antoine Maillard, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Phase retrieval in high dimensions: Statistical and computational phase transitions. CoRR (2020)
Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mézard, Lenka Zdeborová
Generalisation error in learning with random features and the hidden manifold model. CoRR (2020)
Benjamin Aubin, Bruno Loureiro, Antoine Baker, Florent Krzakala, Lenka Zdeborová
Exact asymptotics for phase retrieval and compressed sensing with random generative priors. CoRR (2019)
Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová
The spiked matrix model with generative priors. CoRR (2019)
Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová
The spiked matrix model with generative priors. NeurIPS (2019)
Giannis Kazdaridis, Stratos Keranidis, Polychronis Symeonidis, Paulo Sousa Dias, Pedro Gonçalves, Bruno Loureiro, Petrika Gjanci, Chiara Petrioli
EVERUN: Enabling Power Consumption Monitoring in Underwater Networking Platforms. WiNTECH@MobiCom (2017)