A Random Matrix Perspective of Echo State Networks: From Precise Bias--Variance Characterization to Optimal Regularization
Fuente:
arXiv
Saved in:
| Main Authors: | Moakher, Yessin, Tiomoko, Malik, Louart, Cosme, Liao, Zhenyu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Generalization in Representation Models via Random Matrix Theory: Application to Recurrent Networks
by: Moakher, Yessin, et al.
Published: (2025)
by: Moakher, Yessin, et al.
Published: (2025)
Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
by: Yaakoubi, Chiheb, et al.
Published: (2026)
by: Yaakoubi, Chiheb, et al.
Published: (2026)
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
by: Ilbert, Romain, et al.
Published: (2024)
by: Ilbert, Romain, et al.
Published: (2024)
Optimal Bias-variance Tradeoff in Matrix and Tensor Estimation
by: Kumar, Shivam, et al.
Published: (2025)
by: Kumar, Shivam, et al.
Published: (2025)
Precise Asymptotics and Refined Regret of Variance-Aware UCB
by: Fan, Yingying, et al.
Published: (2024)
by: Fan, Yingying, et al.
Published: (2024)
Random Forests as Statistical Procedures: Design, Variance, and Dependence
by: O'Connell, Nathaniel S.
Published: (2026)
by: O'Connell, Nathaniel S.
Published: (2026)
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
by: Dandi, Yatin, et al.
Published: (2024)
by: Dandi, Yatin, et al.
Published: (2024)
Precise Asymptotics of Bagging Regularized M-estimators
by: Koriyama, Takuya, et al.
Published: (2024)
by: Koriyama, Takuya, et al.
Published: (2024)
The Benefits of Balance: From Information Projections to Variance Reduction
by: Liu, Lang, et al.
Published: (2024)
by: Liu, Lang, et al.
Published: (2024)
High-Dimensional Analysis of Bootstrap Ensemble Classifiers
by: Tiomoko, Malik, et al.
Published: (2025)
by: Tiomoko, Malik, et al.
Published: (2025)
Optimal Ridge Regularization for Out-of-Distribution Prediction
by: Patil, Pratik, et al.
Published: (2024)
by: Patil, Pratik, et al.
Published: (2024)
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
by: Byambadalai, Undral, et al.
Published: (2024)
by: Byambadalai, Undral, et al.
Published: (2024)
Universal concentration for sums under arbitrary dependence
by: Louart, Cosme, et al.
Published: (2026)
by: Louart, Cosme, et al.
Published: (2026)
Non-Asymptotic Analysis of Data Augmentation for Precision Matrix Estimation
by: Morisset, Lucas, et al.
Published: (2025)
by: Morisset, Lucas, et al.
Published: (2025)
UTICA: Multi-Objective Self-Distllation Foundation Model Pretraining for Time Series Classification
by: Moakher, Yessin, et al.
Published: (2026)
by: Moakher, Yessin, et al.
Published: (2026)
Minimax Optimal Variance-Aware Regret Bounds for Multinomial Logistic MDPs
by: Boudart, Pierre, et al.
Published: (2026)
by: Boudart, Pierre, et al.
Published: (2026)
Resolvent convergence for sample covariance matrices with general covariance profiles and quadratic-form control
by: Louart, Cosme
Published: (2021)
by: Louart, Cosme
Published: (2021)
Random Matrix Theory of Early-Stopped Gradient Flow: A Transient BBP Scenario
by: Coeurdoux, Florentin, et al.
Published: (2026)
by: Coeurdoux, Florentin, et al.
Published: (2026)
Variance estimation in graphs with the fused lasso
by: Padilla, Oscar Hernan Madrid
Published: (2022)
by: Padilla, Oscar Hernan Madrid
Published: (2022)
Variance Reduction for the Independent Metropolis Sampler
by: Liu, Siran, et al.
Published: (2024)
by: Liu, Siran, et al.
Published: (2024)
CARE: Large Precision Matrix Estimation for Compositional Data
by: Zhang, Shucong, et al.
Published: (2023)
by: Zhang, Shucong, et al.
Published: (2023)
Characterizing the Generalization Error of Random Feature Regression with Arbitrary Data-Augmentation
by: Morisset, Lucas, et al.
Published: (2026)
by: Morisset, Lucas, et al.
Published: (2026)
On the Variance, Admissibility, and Stability of Empirical Risk Minimization
by: Kur, Gil, et al.
Published: (2023)
by: Kur, Gil, et al.
Published: (2023)
Variance-Aware Estimation of Kernel Mean Embedding
by: Wolfer, Geoffrey, et al.
Published: (2022)
by: Wolfer, Geoffrey, et al.
Published: (2022)
Adaptive Split Balancing for Optimal Random Forest
by: Zhang, Yuqian, et al.
Published: (2024)
by: Zhang, Yuqian, et al.
Published: (2024)
Orthogonal Approximate Message Passing with Optimal Spectral Initializations for Rectangular Spiked Matrix Models
by: Chen, Haohua, et al.
Published: (2025)
by: Chen, Haohua, et al.
Published: (2025)
Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
by: Dang, Hien, et al.
Published: (2026)
by: Dang, Hien, et al.
Published: (2026)
On the Interpolation Error of Nonlinear Attention versus Linear Regression
by: Liao, Zhenyu, et al.
Published: (2025)
by: Liao, Zhenyu, et al.
Published: (2025)
Precise analysis of ridge interpolators under heavy correlations -- a Random Duality Theory view
by: Stojnic, Mihailo
Published: (2024)
by: Stojnic, Mihailo
Published: (2024)
Jackknife Variance Estimation for Hájek-Dominated Generalized U-Statistics
by: Juergens, Jakob R.
Published: (2025)
by: Juergens, Jakob R.
Published: (2025)
Fixed-Confidence Best Arm Identification with Decreasing Variance
by: Roychowdhury, Tamojeet, et al.
Published: (2025)
by: Roychowdhury, Tamojeet, et al.
Published: (2025)
Locally Optimal Fixed-Budget Best Arm Identification in Two-Armed Gaussian Bandits with Unknown Variances
by: Kato, Masahiro
Published: (2023)
by: Kato, Masahiro
Published: (2023)
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
by: Zhang, Yihan, et al.
Published: (2024)
by: Zhang, Yihan, et al.
Published: (2024)
Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery
by: Kovačević, Filip, et al.
Published: (2025)
by: Kovačević, Filip, et al.
Published: (2025)
Near-Optimal Regret for KL-Regularized Multi-Armed Bandits
by: Ji, Kaixuan, et al.
Published: (2026)
by: Ji, Kaixuan, et al.
Published: (2026)
Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon
by: Yu, Hao
Published: (2025)
by: Yu, Hao
Published: (2025)
Signal-Plus-Noise Decomposition of Nonlinear Spiked Random Matrix Models
by: Moniri, Behrad, et al.
Published: (2024)
by: Moniri, Behrad, et al.
Published: (2024)
Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
by: Firdoussi, Aymane El, et al.
Published: (2024)
by: Firdoussi, Aymane El, et al.
Published: (2024)
Optimality of Approximate Message Passing Algorithms for Spiked Matrix Models with Rotationally Invariant Noise
by: Dudeja, Rishabh, et al.
Published: (2024)
by: Dudeja, Rishabh, et al.
Published: (2024)
Bias-Corrected Joint Spectral Embedding for Multilayer Networks with Invariant Subspace: Entrywise Eigenvector Perturbation and Inference
by: Xie, Fangzheng
Published: (2024)
by: Xie, Fangzheng
Published: (2024)
Similar Items
-
Generalization in Representation Models via Random Matrix Theory: Application to Recurrent Networks
by: Moakher, Yessin, et al.
Published: (2025) -
Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
by: Yaakoubi, Chiheb, et al.
Published: (2026) -
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
by: Ilbert, Romain, et al.
Published: (2024) -
Optimal Bias-variance Tradeoff in Matrix and Tensor Estimation
by: Kumar, Shivam, et al.
Published: (2025) -
Precise Asymptotics and Refined Regret of Variance-Aware UCB
by: Fan, Yingying, et al.
Published: (2024)