Saved in:
| Main Authors: | Gerbelot, Cedric, Troiani, Emanuele, Mignacco, Francesca, Krzakala, Florent, Zdeborova, Lenka |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2210.06591 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks
by: Erba, Vittorio, et al.
Published: (2025)
by: Erba, Vittorio, et al.
Published: (2025)
Multi-layer State Evolution Under Random Convolutional Design
by: Daniels, Mara, et al.
Published: (2022)
by: Daniels, Mara, et al.
Published: (2022)
Bayes-optimal learning of an extensive-width neural network from quadratically many samples
by: Maillard, Antoine, et al.
Published: (2024)
by: Maillard, Antoine, et al.
Published: (2024)
Single-Head Attention in High Dimensions: A Theory of Generalization, Weights Spectra, and Scaling Laws
by: Boncoraglio, Fabrizio, et al.
Published: (2025)
by: Boncoraglio, Fabrizio, et al.
Published: (2025)
Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications
by: Xu, Yizhou, et al.
Published: (2025)
by: Xu, Yizhou, et al.
Published: (2025)
Bayes optimal learning of attention-indexed models
by: Boncoraglio, Fabrizio, et al.
Published: (2025)
by: Boncoraglio, Fabrizio, et al.
Published: (2025)
Fundamental limits of learning in sequence multi-index models and deep attention networks: High-dimensional asymptotics and sharp thresholds
by: Troiani, Emanuele, et al.
Published: (2025)
by: Troiani, Emanuele, et al.
Published: (2025)
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents
by: Dandi, Yatin, et al.
Published: (2024)
by: Dandi, Yatin, et al.
Published: (2024)
Fundamental computational limits of weak learnability in high-dimensional multi-index models
by: Troiani, Emanuele, et al.
Published: (2024)
by: Troiani, Emanuele, et al.
Published: (2024)
Universality laws for Gaussian mixtures in generalized linear models
by: Dandi, Yatin, et al.
Published: (2023)
by: Dandi, Yatin, et al.
Published: (2023)
Statistical mechanics of the maximum-average submatrix problem
by: Erba, Vittorio, et al.
Published: (2023)
by: Erba, Vittorio, et al.
Published: (2023)
Learning with Restricted Boltzmann Machines: Asymptotics of AMP and GD in High Dimensions
by: Xu, Yizhou, et al.
Published: (2025)
by: Xu, Yizhou, et al.
Published: (2025)
Gibbs Sampling the Posterior of Neural Networks
by: Piccioli, Giovanni, et al.
Published: (2023)
by: Piccioli, Giovanni, et al.
Published: (2023)
Gaussian Universality of Perceptrons with Random Labels
by: Gerace, Federica, et al.
Published: (2022)
by: Gerace, Federica, et al.
Published: (2022)
Stochastic gradient descent in high dimensions for multi-spiked tensor PCA
by: Arous, Gérard Ben, et al.
Published: (2024)
by: Arous, Gérard Ben, et al.
Published: (2024)
Fundamental limits of Non-Linear Low-Rank Matrix Estimation
by: Mergny, Pierre, et al.
Published: (2024)
by: Mergny, Pierre, et al.
Published: (2024)
A phase transition between positional and semantic learning in a solvable model of dot-product attention
by: Cui, Hugo, et al.
Published: (2024)
by: Cui, Hugo, et al.
Published: (2024)
The Computational Advantage of Depth: Learning High-Dimensional Hierarchical Functions with Gradient Descent
by: Dandi, Yatin, et al.
Published: (2025)
by: Dandi, Yatin, et al.
Published: (2025)
The phase diagram of compressed sensing with $\ell_0$-norm regularization
by: Barbier, Damien, et al.
Published: (2024)
by: Barbier, Damien, et al.
Published: (2024)
Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime
by: Defilippis, Leonardo, et al.
Published: (2025)
by: Defilippis, Leonardo, et al.
Published: (2025)
Computational Thresholds in Multi-Modal Learning via the Spiked Matrix-Tensor Model
by: Tabanelli, Hugo, et al.
Published: (2025)
by: Tabanelli, Hugo, et al.
Published: (2025)
Analysis of learning a flow-based generative model from limited sample complexity
by: Cui, Hugo, et al.
Published: (2023)
by: Cui, Hugo, et al.
Published: (2023)
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective
by: Ghio, Davide, et al.
Published: (2023)
by: Ghio, Davide, et al.
Published: (2023)
Asymptotic Characterisation of Robust Empirical Risk Minimisation Performance in the Presence of Outliers
by: Vilucchio, Matteo, et al.
Published: (2023)
by: Vilucchio, Matteo, et al.
Published: (2023)
Asymptotics of Non-Convex Generalized Linear Models in High-Dimensions: A proof of the replica formula
by: Vilucchio, Matteo, et al.
Published: (2025)
by: Vilucchio, Matteo, et al.
Published: (2025)
Long-time dynamics and universality of nonconvex gradient descent
by: Han, Qiyang
Published: (2025)
by: Han, Qiyang
Published: (2025)
Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks
by: Arnaboldi, Luca, et al.
Published: (2025)
by: Arnaboldi, Luca, et al.
Published: (2025)
Asymptotics of feature learning in two-layer networks after one gradient-step
by: Cui, Hugo, et al.
Published: (2024)
by: Cui, Hugo, et al.
Published: (2024)
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens
by: Erba, Vittorio, et al.
Published: (2024)
by: Erba, Vittorio, et al.
Published: (2024)
Low-rank Matrix Estimation with Inhomogeneous Noise
by: Guionnet, Alice, et al.
Published: (2022)
by: Guionnet, Alice, et al.
Published: (2022)
Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression
by: Clarté, Lucas, et al.
Published: (2024)
by: Clarté, Lucas, et al.
Published: (2024)
Spectral Thresholds in Correlated Spiked Models and Fundamental Limits of Partial Least Squares
by: Mergny, Pierre, et al.
Published: (2025)
by: Mergny, Pierre, et al.
Published: (2025)
The committee machine: Computational to statistical gaps in learning a two-layers neural network
by: Aubin, Benjamin, et al.
Published: (2018)
by: Aubin, Benjamin, et al.
Published: (2018)
A solvable high-dimensional model where nonlinear autoencoders learn structure invisible to PCA while test loss misaligns with generalization
by: Mendes, Vicente Conde, et al.
Published: (2026)
by: Mendes, Vicente Conde, et al.
Published: (2026)
Statistical Inference and Quality Measures of KV Cache Quantisations Inspired by TurboQuant
by: D'Alberto, Paolo
Published: (2026)
by: D'Alberto, Paolo
Published: (2026)
A learning theory for quantum photonic processors and beyond
by: Rosati, Matteo
Published: (2022)
by: Rosati, Matteo
Published: (2022)
Langevin dynamics for high-dimensional optimization: the case of multi-spiked tensor PCA
by: Arous, Gérard Ben, et al.
Published: (2024)
by: Arous, Gérard Ben, et al.
Published: (2024)
eGAD! double descent is explained by Generalized Aliasing Decomposition
by: Transtrum, Mark K., et al.
Published: (2024)
by: Transtrum, Mark K., et al.
Published: (2024)
A Fast Binary Splitting Approach for Non-Adaptive Learning of Erdős--Rényi Graphs
by: Ta, Hoang, et al.
Published: (2025)
by: Ta, Hoang, et al.
Published: (2025)
Universality of high-dimensional scaling limits of stochastic gradient descent
by: Gheissari, Reza, et al.
Published: (2025)
by: Gheissari, Reza, et al.
Published: (2025)
Similar Items
-
The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks
by: Erba, Vittorio, et al.
Published: (2025) -
Multi-layer State Evolution Under Random Convolutional Design
by: Daniels, Mara, et al.
Published: (2022) -
Bayes-optimal learning of an extensive-width neural network from quadratically many samples
by: Maillard, Antoine, et al.
Published: (2024) -
Single-Head Attention in High Dimensions: A Theory of Generalization, Weights Spectra, and Scaling Laws
by: Boncoraglio, Fabrizio, et al.
Published: (2025) -
Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications
by: Xu, Yizhou, et al.
Published: (2025)