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Long random matrices and tensor unfolding (Q6180391)

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scientific article; zbMATH DE number 7791546

Language	Label	Description	Also known as
English	Long random matrices and tensor unfolding	scientific article; zbMATH DE number 7791546

Statements

scholarly article

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Long random matrices and tensor unfolding (English)

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Gérard Ben Arous

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Daniel Z. Huang

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The Annals of Applied Probability

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publication date

19 January 2024

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full work available at URL

https://arxiv.org/abs/2110.10210

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zbMATH Keywords

random matrices

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tensor PCA

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MaRDI profile type

MaRDI publication profile

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On sample eigenvalues in a generalized spiked population model

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Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices

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Eigenvalues of large sample covariance matrices of spiked population models

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Notes on computational-to-statistical gaps: predictions using statistical physics

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Eigenvector distribution in the critical regime of BBP transition

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Algorithmic thresholds for tensor PCA

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The Landscape of the Spiked Tensor Model

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Fluctuations of the extreme eigenvalues of finite rank deformations of random matrices

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The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices

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The singular values and vectors of low rank perturbations of large rectangular random matrices

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Minimax bounds for sparse PCA with noisy high-dimensional data

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How to iron out rough landscapes and get optimal performances: averaged gradient descent and its application to tensor PCA

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Isotropic local laws for sample covariance and generalized Wigner matrices

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Optimal estimation and rank detection for sparse spiked covariance matrices

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Sparse PCA: optimal rates and adaptive estimation

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Phase transition in the spiked random tensor with Rademacher prior

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A Multilinear Singular Value Decomposition

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On the Best Rank-1 and Rank-(<i>R</i><sub>1</sub> ,<i>R</i><sub>2</sub> ,. . .,<i>R<sub>N</sub></i>) Approximation of Higher-Order Tensors

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Optimal shrinkage of eigenvalues in the spiked covariance model

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Spectrum estimation for large dimensional covariance matrices using random matrix theory

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Spiked singular values and vectors under extreme aspect ratios

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Tensor Spaces and Numerical Tensor Calculus

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An optimal statistical and computational framework for generalized tensor estimation

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Phase transition in random tensors with multiple independent spikes

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Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors

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Mesoscopic perturbations of large random matrices

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Statistical thresholds for tensor PCA

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On the distribution of the largest eigenvalue in principal components analysis

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On Consistency and Sparsity for Principal Components Analysis in High Dimensions

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Nonlinear shrinkage estimation of large-dimensional covariance matrices

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Tensor clustering with planted structures: statistical optimality and computational limits

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Sparse principal component analysis and iterative thresholding

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Asymptotic power of sphericity tests for high-dimensional data

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Statistical limits of spiked tensor models

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Optimality and sub-optimality of PCA. I: Spiked random matrix models

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Tensor Decomposition for Signal Processing and Machine Learning

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Minimax sparse principal subspace estimation in high dimensions

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Tensor SVD: Statistical and Computational Limits

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Tensor Regression with Applications in Neuroimaging Data Analysis

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Identifiers

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Mathematics Subject Classification ID

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zbMATH DE Number

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10.1214/23-AAP1958

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Sitelinks

Mathematics(1 entry)

mardi Publication:6180391

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