Pages that link to "Item:Q2343031"

The following pages link to Optimal estimation and rank detection for sparse spiked covariance matrices (Q2343031):

Displaying 50 items.

• Posterior contraction rates of the phylogenetic Indian buffet processes (Q516479) (← links)
• Minimax rate-optimal estimation of high-dimensional covariance matrices with incomplete data (Q739584) (← links)
• Optimal sparse eigenspace and low-rank density matrix estimation for quantum systems (Q830705) (← links)
• Minimax estimation in sparse canonical correlation analysis (Q888508) (← links)
• Estimation of functionals of sparse covariance matrices (Q892255) (← links)
• Recent developments in high dimensional covariance estimation and its related issues, a review (Q1657856) (← links)
• On two-sample mean tests under spiked covariances (Q1661347) (← links)
• Random perturbation of low rank matrices: improving classical bounds (Q1688904) (← links)
• Video denoising via empirical Bayesian estimation of space-time patches (Q1701995) (← links)
• The spectral norm of random inner-product kernel matrices (Q1729691) (← links)
• Robust covariance estimation for approximate factor models (Q1739628) (← links)
• Rate-optimal perturbation bounds for singular subspaces with applications to high-dimensional statistics (Q1747733) (← links)
• Robust covariance and scatter matrix estimation under Huber's contamination model (Q1800790) (← links)
• Optimality and sub-optimality of PCA. I: Spiked random matrix models (Q1800806) (← links)
• Test for high dimensional covariance matrices (Q1996783) (← links)
• Subspace estimation from unbalanced and incomplete data matrices: \({\ell_{2,\infty}}\) statistical guarantees (Q2039795) (← links)
• Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence (Q2073208) (← links)
• Optimal signal detection in some spiked random matrix models: likelihood ratio tests and linear spectral statistics (Q2091821) (← links)
• Relative perturbation bounds with applications to empirical covariance operators (Q2111217) (← links)
• Estimation of conditional mean operator under the bandable covariance structure (Q2136639) (← links)
• Targeted principal components regression (Q2140873) (← links)
• Lower bounds for invariant statistical models with applications to principal component analysis (Q2157446) (← links)
• Consistent estimation of high-dimensional factor models when the factor number is over-estimated (Q2192324) (← links)
• Limiting laws for divergent spiked eigenvalues and largest nonspiked eigenvalue of sample covariance matrices (Q2196219) (← links)
• Statistical and computational limits for sparse matrix detection (Q2196237) (← links)
• Bayesian bandwidth test and selection for high-dimensional banded precision matrices (Q2226705) (← links)
• Shrinkage priors for single-spiked covariance models (Q2244463) (← links)
• Subspace perspective on canonical correlation analysis: dimension reduction and minimax rates (Q2278668) (← links)
• Minimax posterior convergence rates and model selection consistency in high-dimensional DAG models based on sparse Cholesky factors (Q2284379) (← links)
• Compressed covariance estimation with automated dimension learning (Q2300095) (← links)
• Testing and estimating change-points in the covariance matrix of a high-dimensional time series (Q2306269) (← links)
• ROP: matrix recovery via rank-one projections (Q2338922) (← links)
• Rate-optimal posterior contraction for sparse PCA (Q2343963) (← links)
• Large covariance estimation through elliptical factor models (Q2413594) (← links)
• Optimal shrinkage of eigenvalues in the spiked covariance model (Q2413608) (← links)
• Sparse PCA: optimal rates and adaptive estimation (Q2443213) (← links)
• Signal detection in high dimension: the multispiked case (Q2448730) (← links)
• Matrix means and a novel high-dimensional shrinkage phenomenon (Q2676932) (← links)
• Estimation of Wasserstein distances in the spiked transport model (Q2676937) (← links)
• Tracy-Widom limit for the largest eigenvalue of high-dimensional covariance matrices in elliptical distributions (Q2676949) (← links)
• Near-optimal estimation of simultaneously sparse and low-rank matrices from nested linear measurements (Q4603729) (← links)
• ECA: High-Dimensional Elliptical Component Analysis in Non-Gaussian Distributions (Q4690955) (← links)
• Detecting changes in the second moment structure of high-dimensional sensor-type data in a <i>K</i>-sample setting (Q4965652) (← links)
• Estimating Large Precision Matrices via Modified Cholesky Decomposition (Q4986367) (← links)
• (Q4998937) (← links)
• (Q5004041) (← links)
• Gaussian Patch Mixture Model Guided Low-Rank Covariance Matrix Minimization for Image Denoising (Q5056914) (← links)
• Fast Estimation of Approximate Matrix Ranks Using Spectral Densities (Q5380703) (← links)
• Estimating structured high-dimensional covariance and precision matrices: optimal rates and adaptive estimation (Q5965313) (← links)
• Discussion of ``Estimating structured high-dimensional covariance and precision matrices: optimal rates and adaptive estimation'' (Q5965315) (← links)