Shrinkage Algorithms for MMSE Covariance Estimation

27 July 2009

Papers citing "Shrinkage Algorithms for MMSE Covariance Estimation"

41 / 41 papers shown

Title
Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry Antoine Collas Ce Ju Nicolas Salvy Bertrand Thirion 53 0 0 20 May 2025
Scalable Geometric Learning with Correlation-Based Functional Brain Networks Kisung You Yelim Lee Hae-Jeong Park 109 0 0 31 Mar 2025
Analysis of a multi-target linear shrinkage covariance estimator Benoit Oriol 114 0 0 13 Mar 2025
Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices Thibault de Surrel Fabien Lotte Sylvain Chevallier Florian Yger 159 1 0 03 Feb 2025
A Pluggable Common Sense-Enhanced Framework for Knowledge Graph Completion Guanglin Niu Bo Li Siling Feng 54 0 0 06 Oct 2024
Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure Can Pouliquen Mathurin Massias Titouan Vayer 168 0 0 13 Jun 2024
Regularized Linear Discriminant Analysis Using a Nonlinear Covariance Matrix Estimator Maaz Mahadi Tarig Ballal M. Moinuddin Tareq Y. Al-Naffouri U. M. Al-Saggaf 55 5 0 31 Jan 2024
Ledoit-Wolf linear shrinkage with unknown mean Benoit Oriol Alexandre Miot 65 3 0 14 Apr 2023
Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems G. S. Gusmão A. Medford PINN 52 9 0 12 Apr 2023
Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters Marloes Arts J. Frellsen Wouter Boomsma 74 1 0 27 Feb 2023
Distributional Robustness Bounds Generalization Errors Shixiong Wang Haowei Wang OOD 90 4 0 20 Dec 2022
Unequal Covariance Awareness for Fisher Discriminant Analysis and Its Variants in Classification Thu Nguyen Quang M. Le Son N. T. Tu Binh T. Nguyen 24 1 0 26 May 2022
Sparsification and Filtering for Spatial-temporal GNN in Multivariate Time-series Yuanrong Wang T. Aste AI4TS 55 10 0 08 Mar 2022
Unifying Pairwise Interactions in Complex Dynamics Oliver M. Cliff Annie G. Bryant J. Lizier N. Tsuchiya Ben D. Fulcher 69 41 0 28 Jan 2022
Learning with latent group sparsity via heat flow dynamics on networks Subhro Ghosh Soumendu Sundar Mukherjee AI4CE 65 2 0 20 Jan 2022
Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification Myriam Bontonou Nicolas Farrugia Vincent Gripon CML 47 0 0 23 Aug 2021
On the interpretation of linear Riemannian tangent space model parameters in M/EEG Reinmar J. Kobler J. Hirayama Lea Hehenberger G. Müller-Putz M. Kawanabe 57 11 0 30 Jul 2021
Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis Guillaume Staerman Pavlo Mozharovskyi Stephan Clémençon 180 10 0 21 Jun 2021
Robust learning from corrupted EEG with dynamic spatial filtering Hubert J. Banville Sean U. N. Wood Chris Aimone Denis A. Engemann Alexandre Gramfort 58 32 0 27 May 2021
Class-Incremental Learning with Generative Classifiers Gido M. van de Ven Zhe Li A. Tolias BDL 96 60 0 20 Apr 2021
High-Dimensional Covariance Shrinkage for Signal Detection Benjamin D. Robinson Robert Malinas Alfred Hero 43 1 0 22 Mar 2021
Coupled regularized sample covariance matrix estimator for multiple classes Elias Raninen Esa Ollila 14 7 0 09 Nov 2020
Post-selection inference with HSIC-Lasso Tobias Freidling B. Poignard Héctor Climente-González M. Yamada 76 14 0 29 Oct 2020
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat Jennifer Gillenwater Eric Xing Afshin Rostamizadeh FedML 126 112 0 11 Oct 2020
Stochastically forced ensemble dynamic mode decomposition for forecasting and analysis of near-periodic systems D. Dylewsky D. Barajas-Solano Tong Ma A. Tartakovsky J. Nathan Kutz AI4TS 58 16 0 08 Oct 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 79 32 0 09 Jun 2020
A Compressive Classification Framework for High-Dimensional Data Muhammad Naveed Tabassum Esa Ollila 18 0 0 09 May 2020
M-estimators of scatter with eigenvalue shrinkage Esa Ollila Daniel P. Palomar Frédéric Pascal 37 2 0 12 Feb 2020
Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon A. Lodhia Keith D. Levin Elizaveta Levina 30 3 0 16 Oct 2019
Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis Tyler L. Hayes Christopher Kanan CLL 70 144 0 04 Sep 2019
Adaptive Shrinkage Estimation for Streaming Graphs Nesreen Ahmed N. Duffield 20 2 0 02 Aug 2019
Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization Qilong Wang Jiangtao Xie W. Zuo Lei Zhang P. Li 81 99 0 15 Apr 2019
MOABB: Trustworthy algorithm benchmarking for BCIs V. Jayaram A. Barachant 58 180 0 16 May 2018
Multi-Step Knowledge-Aided Iterative ESPRIT for Direction Finding Silvio F. B. Pinto R. D. Lamare 16 7 0 01 May 2018
Is Second-order Information Helpful for Large-scale Visual Recognition? P. Li Jiangtao Xie Qilong Wang W. Zuo FAtt 85 251 0 23 Mar 2017
Numerical Implementation of the QuEST Function Olivier Ledoit Michael Wolf 46 70 0 22 Jan 2016
Regularized estimation of linear functionals of precision matrices for high-dimensional time series Xiaohui Chen Mengyu Xu Wei Biao Wu 99 25 0 11 Jun 2015
Subspace Leakage Analysis and Improved DOA Estimation with Small Sample Size M. Shaghaghi S. Vorobyov 62 76 0 31 Jan 2015
An RKHS Approach to Estimation with Sparsity Constraints A. Jung 86 3 0 22 Nov 2013
Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model D. Donoho M. Gavish Iain M. Johnstone 190 208 0 04 Nov 2013
Adaptive Evolutionary Clustering Kevin S. Xu M. Kliger Alfred Hero 83 135 0 11 Apr 2011