Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model

4 November 2013

Papers citing "Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model"

38 / 88 papers shown

Title
Regularization in High-Dimensional Regression and Classification via Random Matrix Theory Panagiotis Lolas 43 13 0 30 Mar 2020
Geodesically parameterized covariance estimation A. Musolas S.T. Smith Youssef Marzouk 20 4 0 06 Jan 2020
A note on identifiability conditions in confirmatory factor analysis W. Leeb CML 9 4 0 05 Dec 2019
Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon A. Lodhia Keith D. Levin Elizaveta Levina 26 3 0 16 Oct 2019
Asymptotics of empirical eigenvalues for large separable covariance matrices Tiebin Mi Robert C. Qiu 34 0 0 10 Oct 2019
Spiked separable covariance matrices and principal components Xiucai Ding Fan Yang 25 56 0 29 May 2019
Rapid evaluation of the spectral signal detection threshold and Stieltjes transform W. Leeb 31 7 0 26 Apr 2019
Optimal Recovery of Precision Matrix for Mahalanobis Distance from High Dimensional Noisy Observations in Manifold Learning M. Gavish Ronen Talmon P. Su Hau‐Tieng Wu 30 8 0 19 Apr 2019
Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization Qilong Wang Jiangtao Xie W. Zuo Lei Zhang P. Li 25 99 0 15 Apr 2019
Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification L. Duan 30 9 0 21 Mar 2019
Matrix denoising for weighted loss functions and heterogeneous signals W. Leeb 32 25 0 25 Feb 2019
Statistical inference with F-statistics when fitting simple models to high-dimensional data Hannes Leeb Lukas Steinberger 17 1 0 12 Feb 2019
Robust Streaming PCA D. Bienstock Minchan Jeong Apurv Shukla Se-Young Yun 20 3 0 08 Feb 2019
Steerable $e$ PCA: Rotationally Invariant Exponential Family PCA Zhizhen Zhao Lydia T. Liu A. Singer 17 3 0 20 Dec 2018
Optimal spectral shrinkage and PCA with heteroscedastic noise Qiangqiang Wu Yanjie Liang 30 25 0 06 Nov 2018
RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding Rajen Dinesh Shah Benjamin Frot Gian-Andrea Thanei N. Meinshausen 19 6 0 02 Nov 2018
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data David Hong Fan Yang Jeffrey A. Fessler Laura Balzano 21 25 0 30 Oct 2018
Heteroskedastic PCA: Algorithm, Optimality, and Applications Anru R. Zhang T. Tony Cai Yihong Wu 32 70 0 19 Oct 2018
Optimal Covariance Estimation for Condition Number Loss in the Spiked Model D. Donoho Behrooz Ghorbani 111 7 0 17 Oct 2018
Adapting to Unknown Noise Distribution in Matrix Denoising Andrea Montanari Feng Ruan Jun Yan 31 13 0 06 Oct 2018
Harmonic Alignment Jay S. Stanley Scott A. Gigante Guy Wolf Smita Krishnaswamy DiffM 32 16 0 30 Sep 2018
Robust high dimensional factor models with applications to statistical machine learning Jianqing Fan Kaizheng Wang Yiqiao Zhong Ziwei Zhu 34 54 0 12 Aug 2018
Estimating Learnability in the Sublinear Data Regime Weihao Kong Gregory Valiant 45 29 0 04 May 2018
Graph-based regularization for regression problems with alignment and highly-correlated designs Yuan Li Benjamin Mark Garvesh Raskutti Rebecca Willett Hyebin Song David Neiman 14 23 0 20 Mar 2018
Multidimensional Scaling of Noisy High Dimensional Data Erez Peterfreund M. Gavish 19 21 0 30 Jan 2018
The Dispersion Bias L. Goldberg A. Papanicolaou Alexander D. Shkolnik 34 15 0 15 Nov 2017
Tail sums of Wishart and GUE eigenvalues beyond the bulk edge Iain M. Johnstone 22 1 0 21 Apr 2017
Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals A. Beskos Ajay Jasra K. Law Youssef Marzouk Yan Zhou 20 40 0 15 Mar 2017
Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding Hau‐Tieng Wu Nan Wu 8 40 0 12 Mar 2017
PCA from noisy, linearly reduced data: the diagonal case Edgar Dobriban W. Leeb A. Singer 26 5 0 30 Nov 2016
Graph-Guided Banding of the Covariance Matrix Jacob Bien 19 6 0 01 Jun 2016
Denoising and Covariance Estimation of Single Particle Cryo-EM Images T. Bhamre Teng Zhang A. Singer 21 64 0 22 Feb 2016
Latent common manifold learning with alternating diffusion: analysis and applications Ronen Talmon Hau‐Tieng Wu MedIm 27 44 0 30 Jan 2016
Spectrum Estimation from Samples Weihao Kong Gregory Valiant 18 72 0 30 Jan 2016
Newton-Stein Method: An optimization method for GLMs via Stein's Lemma Murat A. Erdogdu 29 13 0 28 Nov 2015
Towards Effective Codebookless Model for Image Classification Qilong Wang P. Li Lei Zhang W. Zuo 16 31 0 09 Jul 2015
Fast Steerable Principal Component Analysis Zhizhen Zhao Y. Shkolnisky A. Singer 29 70 0 02 Dec 2014
Optimal Shrinkage of Singular Values M. Gavish D. Donoho 47 181 0 29 May 2014