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Please use this page instead for the normal view: scientific article; zbMATH DE number 7370563

scientific article; zbMATH DE number 7370563

Language	Label	Description	Also known as
English	No label defined	scientific article; zbMATH DE number 7370563

Statements

scholarly article

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publication date

9 July 2021

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full work available at URL

https://arxiv.org/abs/2002.07624

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https://jmlr.csail.mit.edu/papers/v22/20-610.html

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zbMATH Keywords

low-rank matrix

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metric entropy

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minimax risk

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principal component analysis

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singular value decomposition

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describes a project that uses

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MaRDI profile type

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Entrywise eigenvector analysis of random matrices with low expected rank

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On decoupling, series expansions, and tail behavior of chaos processes

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Central limit theorems for eigenvalues in a spiked population model

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Eigenvalues of large sample covariance matrices of spiked population models

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Tightness of the maximum likelihood semidefinite relaxation for angular synchronization

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Singular vector and singular subspace distribution for the matrix denoising model

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10.1162/153244303321897690

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Minimax bounds for sparse PCA with noisy high-dimensional data

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Nonconvex phase synchronization

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Rate-optimal perturbation bounds for singular subspaces with applications to high-dimensional statistics

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Sparse PCA: optimal rates and adaptive estimation

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Optimal estimation and rank detection for sparse spiked covariance matrices

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Geometric inference for general high-dimensional linear inverse problems

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Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements

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The Projected Power Method: An Efficient Algorithm for Joint Alignment from Pairwise Differences

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Selecting the number of principal components: estimation of the true rank of a noisy matrix

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Minimax risk of matrix denoising by singular value thresholding

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Optimal shrinkage of eigenvalues in the spiked covariance model

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Projections onto convex sets on the sphere

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Partial recovery bounds for clustering with the relaxed \(K\)-means

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Mutual information, metric entropy and cumulative relative entropy risk

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Phase transitions in semidefinite relaxations

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Influential features PCA for high dimensional clustering

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Phase transitions for high dimensional clustering and related problems

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On the distribution of the largest eigenvalue in principal components analysis

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Generalized power method for sparse principal component analysis

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Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)

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Suprema of Chaos Processes and the Restricted Isometry Property

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Aggregation via empirical risk minimization

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Probability in Banach spaces. Isoperimetry and processes

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Adaptive model selection using empirical complexities

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Sparse principal component analysis and iterative thresholding

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Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.

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Non-Negative Principal Component Analysis: Message Passing Algorithms and Sharp Asymptotics

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

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Empirical entropy, minimax regret and minimax risk

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Iterative reconstruction of rank-one matrices in noise

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Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls

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Sparse principal component analysis via regularized low rank matrix approximation

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Angular synchronization by eigenvectors and semidefinite programming

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Upper and Lower Bounds for Stochastic Processes

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Introduction to nonparametric estimation

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High-Dimensional Probability

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Minimax risks for sparse regressions: ultra-high dimensional phenomenons

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Minimax sparse principal subspace estimation in high dimensions

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Asymptotics of empirical eigenstructure for high dimensional spiked covariance

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A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis

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Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation

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Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices

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Minimax nonparametric classification .I. Rates of convergence

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Information-theoretic determination of minimax rates of convergence

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A lower bound on the error in nonparametric regression type problems

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Identifiers

Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:4998937

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