Lenka Zdeborová

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 158

Top Venues

Publications

Christian Keup, Lenka Zdeborová
Optimal thresholds and algorithms for a model of multi-modal learning in high dimensions. CoRR (2024)
Rayan Harfouche, Giovanni Piccioli, Lenka Zdeborová
Integer Traffic Assignment Problem: Algorithms and Insights on Random Graphs. CoRR (2024)
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborová
Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity. ICLR (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)
Odilon Duranthon, Lenka Zdeborová
Asymptotic generalization error of a single-layer graph convolutional network. CoRR (2024)
Pierre Mergny, Justin Ko, Florent Krzakala, Lenka Zdeborová
Fundamental limits of Non-Linear Low-Rank Matrix Estimation. CoRR (2024)
Pierre Mergny, Justin Ko, Florent Krzakala, Lenka Zdeborová
Fundamental Limits of Non-Linear Low-Rank Matrix Estimation. COLT (2024)
Hugo Cui, Freya Behrens, Florent Krzakala, Lenka Zdeborová
A phase transition between positional and semantic learning in a solvable model of dot-product attention. 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)
Freya Behrens, Luca Biggio, Lenka Zdeborová
Understanding Counting in Small Transformers: The Interplay between Attention and Feed-Forward Layers. CoRR (2024)
Yatin Dandi, Emanuele Troiani, Luca Arnaboldi, Luca Pesce, Lenka Zdeborová, Florent Krzakala
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents. CoRR (2024)
Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco, Florent Krzakala, Lenka Zdeborová
Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods. SIAM J. Math. Data Sci. 6 (2) (2024)
O. Duranthon, Lenka Zdeborová
Optimal Inference in Contextual Stochastic Block Models. Trans. Mach. Learn. Res. 2024 (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)
Hugo Cui, Lenka Zdeborová
High-dimensional Asymptotics of Denoising Autoencoders. NeurIPS (2023)
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborová
Analysis of learning a flow-based generative model from limited sample complexity. CoRR (2023)
D. Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová
Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. ITW (2023)
Antoine Baker, Florent Krzakala, Benjamin Aubin, Lenka Zdeborová
Tree-AMP: Compositional Inference with Tree Approximate Message Passing. J. Mach. Learn. Res. 24 (2023)
Odilon Duranthon, Lenka Zdeborová
Optimal Inference in Contextual Stochastic Block Models. 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)
D. Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová
Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery. CoRR (2023)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Expectation consistency for calibration of neural networks. UAI (2023)
Sebastian Goldt, Florent Krzakala, Lenka Zdeborová, Nicolas Brunel
Bayesian reconstruction of memories stored in neural networks from their connectivity. PLoS Comput. Biol. 19 (1) (2023)
Odilon Duranthon, Lenka Zdeborová
Neural-prior stochastic block model. Mach. Learn. Sci. Technol. 4 (3) (2023)
Vittorio Erba, Florent Krzakala, Rodrigo Pérez, Lenka Zdeborová
Statistical mechanics of the maximum-average submatrix problem. CoRR (2023)
Davide Ghio, Yatin Dandi, Florent Krzakala, Lenka Zdeborová
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective. CoRR (2023)
Hugo Cui, Florent Krzakala, Lenka Zdeborová
Optimal Learning of Deep Random Networks of Extensive-width. CoRR (2023)
Yatin Dandi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro, Lenka Zdeborová
Universality laws for Gaussian mixtures in generalized linear models. NeurIPS (2023)
Hugo Cui, Lenka Zdeborová
High-dimensional Asymptotics of Denoising Autoencoders. CoRR (2023)
Hugo Cui, Florent Krzakala, Lenka Zdeborová
Bayes-optimal Learning of Deep Random Networks of Extensive-width. ICML (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)
Giovanni Piccioli, Emanuele Troiani, Lenka Zdeborová
Gibbs Sampling the Posterior of Neural Networks. CoRR (2023)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Expectation consistency for calibration of neural networks. CoRR (2023)
Freya Behrens, Gabriel Arpino, Yaroslav Kivva, Lenka Zdeborová
(Dis)assortative Partitions on Random Regular Graphs. CoRR (2022)
Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová
Probing transfer learning with a model of synthetic correlated datasets. Mach. Learn. Sci. Technol. 3 (1) (2022)
Urte Adomaityte, Anshul Toshniwal, Gabriele Sicuro, Lenka Zdeborová
Planted matching problems on random hypergraphs. 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)
Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco, Florent Krzakala, Lenka Zdeborová
Rigorous dynamical mean field theory for stochastic gradient descent methods. CoRR (2022)
Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap. NeurIPS (2022)
Emanuele Troiani, Vittorio Erba, Florent Krzakala, Antoine Maillard, Lenka Zdeborová
Optimal denoising of rotationally invariant rectangular matrices. CoRR (2022)
Max Daniels, Cédric Gerbelot, Florent Krzakala, Lenka Zdeborová
Multi-layer State Evolution Under Random Convolutional Design. CoRR (2022)
Emanuele Troiani, Vittorio Erba, Florent Krzakala, Antoine Maillard, Lenka Zdeborová
Optimal denoising of rotationally invariant rectangular matrices. MSML (2022)
Siyu Chen, Guanhao Huang, Giovanni Piccioli, Lenka Zdeborová
The planted XY model: thermodynamics and inference. CoRR (2022)
Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Subspace clustering in high-dimensions: Phase transitions \& Statistical-to-Computational gap. CoRR (2022)
Max Daniels, Cédric Gerbelot, Florent Krzakala, Lenka Zdeborová
Multi-layer State Evolution Under Random Convolutional Design. NeurIPS (2022)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
A study of uncertainty quantification in overparametrized high-dimensional models. CoRR (2022)
David Gamarnik, Cristopher Moore, Lenka Zdeborová
Disordered Systems Insights on Computational Hardness. CoRR (2022)
Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
Theoretical characterization of uncertainty in high-dimensional linear classification. CoRR (2022)
Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, Cédric Gerbelot, Bruno Loureiro, Lenka Zdeborová
Learning curves for the multi-class teacher-student perceptron. 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. 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)
Francesca Mignacco, Pierfrancesco Urbani, Lenka Zdeborová
Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem. CoRR (2021)
Antoine Maillard, Florent Krzakala, Marc Mézard, Lenka Zdeborová
Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising. CoRR (2021)
Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborová
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. CoRR (2021)
Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová
Probing transfer learning with a model of synthetic correlated datasets. CoRR (2021)
Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Construction of optimal spectral methods in phase retrieval. 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)
Luca Saglietti, Lenka Zdeborová
Solvable Model for Inheriting the Regularization through Knowledge Distillation. MSML (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)
Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborová
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. ICML (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)
Giovanni Piccioli, Guilhem Semerjian, Gabriele Sicuro, Lenka Zdeborová
Aligning random graphs with a sub-tree similarity message-passing algorithm. CoRR (2021)
Francesca Mignacco, Pierfrancesco Urbani, Lenka Zdeborová
Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem. Mach. Learn. Sci. Technol. 2 (3) (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)
Hugo Cui, Luca Saglietti, Lenka Zdeborová
Large deviations in the perceptron model and consequences for active learning. Mach. Learn. Sci. Technol. 2 (4) (2021)
Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. NeurIPS (2020)
Francesca Mignacco, Florent Krzakala, Yue Lu, Pierfrancesco Urbani, Lenka Zdeborová
The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture. ICML (2020)
Luca Saglietti, Lenka Zdeborová
Solvable Model for Inheriting the Regularization through Knowledge Distillation. CoRR (2020)
Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Construction of optimal spectral methods in phase retrieval. CoRR (2020)
Guilhem Semerjian, Gabriele Sicuro, Lenka Zdeborová
Recovery thresholds in the sparse planted matching problem. CoRR (2020)
Antoine Baker, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová
TRAMP: Compositional Inference with TRee Approximate Message Passing. CoRR (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
Epidemic mitigation by statistical inference from contact tracing data. CoRR (2020)
Benjamin Aubin, Bruno Loureiro, Antoine Baker, Florent Krzakala, Lenka Zdeborová
Exact asymptotics for phase retrieval and compressed sensing with random generative priors. MSML (2020)
Gabriele Sicuro, Lenka Zdeborová
The planted k-factor problem. CoRR (2020)
Hugo Cui, Luca Saglietti, Lenka Zdeborová
Large deviations for the perceptron model and consequences for active learning. MSML (2020)
Frédéric Jolivet, Clarisse Fournier, Michel Garcin, Lenka Zdeborová, Andrea Brambilla
An Alternating Projection-Image Domains Algorithm for Spectral CT. ISBI (2020)
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. NeurIPS (2020)
Sebastian Goldt, Galen Reeves, Marc Mézard, Florent Krzakala, Lenka Zdeborová
The Gaussian equivalence of generative models for learning with two-layer neural networks. CoRR (2020)
Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions. NeurIPS (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)
Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification. NeurIPS (2020)
William H. Weir, Benjamin Walker, Lenka Zdeborová, Peter J. Mucha
Multilayer Modularity Belief Propagation to Assess Detectability of Community Structure. SIAM J. Math. Data Sci. 2 (3) (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)
Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification. CoRR (2020)
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. CoRR (2020)
Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
The role of regularization in classification of high-dimensional noisy Gaussian mixture. 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)
Stefano Sarao Mannelli, Lenka Zdeborová
Thresholds of descending algorithms in inference problems. CoRR (2020)
Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions. CoRR (2020)
Alia Abbara, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová
Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning. MSML (2020)
Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. CoRR (2020)
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models. NeurIPS (2019)
Antoine Maillard, Laura Foini, Alejandro Lage Castellanos, Florent Krzakala, Marc Mézard, Lenka Zdeborová
High-temperature Expansions and Message Passing Algorithms. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lenka Zdeborová