Dimension-free bounds for sums of dependent matrices and operators with heavy-tailed distributions
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Publication:6200904
DOI10.1214/24-ejs2224arXiv2210.09756OpenAlexW4392522215MaRDI QIDQ6200904
Pierre Alquier, Masaaki Imaizumi, Shogo H. Nakakita
Publication date: 25 March 2024
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2210.09756
Processes with independent increments; Lévy processes (60G51) Estimation in multivariate analysis (62H12) Matrix methods for summability (40C05)
Cites Work
- Unnamed Item
- Covariance estimation for distributions with \({2+\varepsilon}\) moments
- Model selection for weakly dependent time series forecasting
- Concentration inequalities and moment bounds for sample covariance operators
- Moment bounds for large autocovariance matrices under dependence
- \(L_{p}\)-moments of random vectors via majorizing measures
- Weakly dependent chains with infinite memory
- Optimal rates of convergence for covariance matrix estimation
- Random vectors in the isotropic position
- Robust dimension-free Gram operator estimates
- New dependence coefficients. Examples and applications to statistics
- Adaptive estimation of a quadratic functional by model selection.
- Challenging the empirical mean and empirical variance: a deviation study
- Bootstrapping the operator norm in high dimensions: error estimation for covariance matrices and sketching
- On the sample covariance matrix estimator of reduced effective rank population matrices, with applications to fPCA
- Structured random matrices
- On the singular values of random matrices
- Weak dependence. With examples and applications.
- Non-strong mixing autoregressive processes
- Quantitative estimates of the convergence of the empirical covariance matrix in log-concave ensembles
- Inégalités de Hoeffding pour les fonctions lipschitziennes de suites dépendantes
- High-Dimensional Probability
- <scp>Sub‐Gaussian</scp> Matrices on Sets: Optimal Tail Dependence and Applications
- Benign overfitting in linear regression
- A Simple Tool for Bounding the Deviation of Random Matrices on Geometric Sets
- Compressed sensing
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