Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model

4 November 2013

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

50 / 88 papers shown

Title
Statistical Limits in Random Tensors with Multiple Correlated Spikes Yang Qi Alexis Decurninge 54 0 0 05 Mar 2025
A Pluggable Common Sense-Enhanced Framework for Knowledge Graph Completion Guanglin Niu Bo Li Siling Feng 35 0 0 06 Oct 2024
On the universality of neural encodings in CNNs Florentin Guth Brice Ménard SSL 56 5 0 28 Sep 2024
Optimal Estimation of Structured Covariance Operators Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 43 3 0 04 Aug 2024
A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set Man-Chung Yue Yves Rychener Daniel Kuhn Viet Anh Nguyen 39 1 0 30 May 2024
Model Editing as a Robust and Denoised variant of DPO: A Case Study on Toxicity Rheeya Uppaal Apratim De Yiting He Yiquao Zhong Junjie Hu 46 9 0 22 May 2024
Spectral Properties of Elementwise-Transformed Spiked Matrices Michael J. Feldman 83 3 0 03 Nov 2023
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective Davide Ghio Yatin Dandi Florent Krzakala Lenka Zdeborová DiffM 30 26 0 27 Aug 2023
Multifidelity Covariance Estimation via Regression on the Manifold of Symmetric Positive Definite Matrices A. Maurais Terrence Alsup Benjamin Peherstorfer Youssef Marzouk 38 3 0 23 Jul 2023
Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model Runshi Tang M. Yuan Anru R. Zhang 47 3 0 02 Jul 2023
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models David X. Wu A. Sahai 29 2 0 23 Jun 2023
Uniform error bound for PCA matrix denoising Xin T. Tong Wanjie Wang Yuguan Wang 20 2 0 22 Jun 2023
Analysis and Approximate Inference of Large Random Kronecker Graphs Zhenyu Liao Yuanqian Xia Chengmei Niu Yong Xiao 71 0 0 14 Jun 2023
A Rainbow in Deep Network Black Boxes Florentin Guth Brice Ménard G. Rochette S. Mallat 39 10 0 29 May 2023
On the Noise Sensitivity of the Randomized SVD Elad Romanov 34 0 0 27 May 2023
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA Yuchen Zhou Yuxin Chen 45 4 0 10 Mar 2023
Multi-Fidelity Covariance Estimation in the Log-Euclidean Geometry A. Maurais Terrence Alsup Benjamin Peherstorfer Youssef Marzouk 28 7 0 31 Jan 2023
A CLT for the LSS of large dimensional sample covariance matrices with diverging spikes Zhijun Liu Jiang Hu Z. Bai Haiyan Song 17 6 0 12 Dec 2022
Correlation matrix of equi-correlated normal population: fluctuation of the largest eigenvalue, scaling of the bulk eigenvalues, and stock market Y. Akama 29 3 0 11 Dec 2022
Pitfalls of Climate Network Construction: A Statistical Perspective Moritz Haas B. Goswami U. V. Luxburg 19 4 0 05 Nov 2022
Projection inference for high-dimensional covariance matrices with structured shrinkage targets Fabian Mies A. Steland 32 2 0 04 Nov 2022
Matrix Denoising with Partial Noise Statistics: Optimal Singular Value Shrinkage of Spiked F-Matrices M. Gavish W. Leeb Elad Romanov 16 6 0 02 Nov 2022
Fast Principal Component Analysis for Cryo-EM Images Nicholas F. Marshall Oscar Mickelin Yunpeng Shi A. Singer 22 3 0 31 Oct 2022
Disordered Systems Insights on Computational Hardness D. Gamarnik Cristopher Moore Lenka Zdeborová AI4CE 38 33 0 15 Oct 2022
Optimal Eigenvalue Shrinkage in the Semicircle Limit D. Donoho M. J. Feldman 30 5 0 10 Oct 2022
Large covariance matrix estimation via penalized log-det heuristics E. Bernardi M. Farné 28 0 0 11 Sep 2022
Low-rank Matrix Estimation with Inhomogeneous Noise A. Guionnet Justin Ko Florent Krzakala Lenka Zdeborová 18 16 0 11 Aug 2022
A CLT for the LSS of large dimensional sample covariance matrices with unbounded dispersions Zhijun Liu Jiang Hu Z. Bai Haiyan Song 19 2 0 15 May 2022
Sparsification and Filtering for Spatial-temporal GNN in Multivariate Time-series Yuanrong Wang T. Aste AI4TS 28 10 0 08 Mar 2022
An Improvement on the Hotelling $T^2$ Test Using the Ledoit-Wolf Nonlinear Shrinkage Estimator Benjamin D. Robinson Robert Malinas Van Latimer Beth Bjorkman Morrison Alfred Hero 80 0 0 25 Feb 2022
Long Random Matrices and Tensor Unfolding Gerard Ben Arous Daniel Zhengyu Huang Jiaoyang Huang 41 18 0 19 Oct 2021
James-Stein estimation of the first principal component Alexander D. Shkolnik 22 9 0 05 Sep 2021
Inference for Heteroskedastic PCA with Missing Data Yuling Yan Yuxin Chen Jianqing Fan 43 16 0 26 Jul 2021
Shrinkage Estimation of Functions of Large Noisy Symmetric Matrices Panagiotis Lolas Lexing Ying 37 1 0 09 Jun 2021
Spiked Singular Values and Vectors under Extreme Aspect Ratios M. Feldman 13 9 0 30 Apr 2021
Measuring dependence between random vectors via optimal transport Gilles Mordant Johan Segers OT 14 24 0 28 Apr 2021
High-Dimensional Covariance Shrinkage for Signal Detection Benjamin D. Robinson Robert Malinas Alfred Hero 13 1 0 22 Mar 2021
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization Mathieu Even Laurent Massoulié 24 14 0 04 Feb 2021
Power Iteration for Tensor PCA Jiaoyang Huang Daniel Zhengyu Huang Qing Yang Guang Cheng 33 18 0 26 Dec 2020
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard Mahdi Soltanolkotabi AAML 35 61 0 21 Oct 2020
Detecting approximate replicate components of a high-dimensional random vector with latent structure Xin Bing F. Bunea M. Wegkamp 35 4 0 05 Oct 2020
Shrinkage Estimation of the Frechet Mean in Lie groups Chun-Hao Yang B. Vemuri 6 3 0 28 Sep 2020
Statistical inference for principal components of spiked covariance matrices Z. Bao Xiucai Ding Jingming Wang Ke Wang 20 50 0 27 Aug 2020
Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning Lin Liu Rajarshi Mukherjee J. M. Robins CML 38 16 0 07 Aug 2020
Covariance estimation with nonnegative partial correlations Jake A. Soloff Adityanand Guntuboyina Michael I. Jordan 23 10 0 30 Jul 2020
An Empirical Bayes Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices Chun-Hao Yang Hani Doss B. Vemuri 13 4 0 04 Jul 2020
High-Dimensional Quadratic Discriminant Analysis under Spiked Covariance Model Houssem Sifaou A. Kammoun Mohamed-Slim Alouini 11 8 0 25 Jun 2020
Optimal singular value shrinkage for operator norm loss W. Leeb 17 11 0 24 May 2020
Non-Sparse PCA in High Dimensions via Cone Projected Power Iteration Yufei Yi Matey Neykov 12 2 0 15 May 2020
How to reduce dimension with PCA and random projections? Fan Yang Sifan Liu Yan Sun David P. Woodruff 29 28 0 01 May 2020