Covariance Estimation in High Dimensions via Kronecker Product Expansions

12 February 2013

Papers citing "Covariance Estimation in High Dimensions via Kronecker Product Expansions"

29 / 29 papers shown

Title
DNNLasso: Scalable Graph Learning for Matrix-Variate Data Meixia Lin Yangjing Zhang 36 0 0 05 Mar 2024
Dimension-free Structured Covariance Estimation Nikita Puchkin Maxim Rakhuba 59 1 0 15 Feb 2024
Sharper dimension-free bounds on the Frobenius distance between sample covariance and its expectation Nikita Puchkin Fedor Noskov V. Spokoiny OT 67 7 0 28 Aug 2023
Structured Low-Rank Tensors for Generalized Linear Models Batoul Taki Anand D. Sarwate W. Bajwa 56 2 0 05 Aug 2023
Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model Runshi Tang M. Yuan Anru R. Zhang 97 3 0 02 Jul 2023
On Separability of Covariance in Multiway Data Analysis Dogyoon Song Alfred Hero 56 0 0 05 Feb 2023
Multi-Fidelity Covariance Estimation in the Log-Euclidean Geometry A. Maurais Terrence Alsup Benjamin Peherstorfer Youssef Marzouk 97 7 0 31 Jan 2023
Learning Product Graphs from Spectral Templates A. Einizade S. H. Sardouie 55 6 0 05 Nov 2022
Scalable Bigraphical Lasso: Two-way Sparse Network Inference for Count Data Sijia Li Martín López-García Neil D. Lawrence Luisa Cutillo 53 5 0 15 Mar 2022
Multiway Ensemble Kalman Filter Yu Wang Alfred Hero 56 1 0 08 Dec 2021
Dictionary-based Low-Rank Approximations and the Mixed Sparse Coding problem Jérémy E. Cohen 61 0 0 24 Nov 2021
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in Neuroimaging Ali Hashemi Yijing Gao Chang Cai Sanjay Ghosh Klaus-Robert Muller S. Nagarajan Stefan Haufe 61 7 0 02 Nov 2021
Guaranteed Functional Tensor Singular Value Decomposition Rungang Han Pixu Shi Anru R. Zhang 75 23 0 09 Aug 2021
EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation Jun Ho Yoon Seyoung Kim BDL 43 4 0 20 May 2021
Online Stochastic Gradient Descent Learns Linear Dynamical Systems from A Single Trajectory Navid Reyhanian Jarvis Haupt 45 3 0 23 Feb 2021
Separable Expansions for Covariance Estimation T. Masak Soham Sarkar V. Panaretos 16 0 0 23 Jul 2020
Detection thresholds in very sparse matrix completion C. Bordenave Simon Coste R. Nadakuditi 91 25 0 12 May 2020
Autoregressive Identification of Kronecker Graphical Models Mattia Zorzi 63 16 0 29 Apr 2020
Learning Product Graphs Underlying Smooth Graph Signals M. Lodhi W. Bajwa 64 9 0 26 Feb 2020
Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms Mohsen Ghassemi Z. Shakeri Anand D. Sarwate W. Bajwa 77 16 0 22 Mar 2019
STARK: Structured Dictionary Learning Through Rank-one Tensor Recovery Mohsen Ghassemi Z. Shakeri Anand D. Sarwate W. Bajwa 59 20 0 13 Nov 2017
Matrix-normal models for fMRI analysis Michael Shvartsman N. Sundaram Mikio C. Aoi Adam Charles Theodore L. Willke Jonathan Cohen 54 14 0 08 Nov 2017
Classification and Representation via Separable Subspaces: Performance Limits and Algorithms Ishan Jindal M. Nokleby 46 2 0 07 May 2017
Robust SAR STAP via Kronecker Decomposition Kristjan Greenewald E. Zelnio Alfred Hero 85 25 0 05 May 2016
A Sparse Gaussian Process Framework for Photometric Redshift Estimation I. Almosallam Sam N. Lindsay M. Jarvis Stephen J. Roberts 82 43 0 20 May 2015
Foundational principles for large scale inference: Illustrations through correlation mining Alfred Hero B. Rajaratnam 91 17 0 11 May 2015
Kronecker PCA Based Spatio-Temporal Modeling of Video for Dismount Classification Kristjan Greenewald Alfred Hero 67 9 0 19 May 2014
Detection of Anomalous Crowd Behavior Using Spatio-Temporal Multiresolution Model and Kronecker Sum Decompositions Kristjan Greenewald Alfred Hero 110 8 0 14 Jan 2014
Kronecker Sum Decompositions of Space-Time Data Kristjan Greenewald Theodoros Tsiligkaridis Alfred Hero 115 25 0 27 Jul 2013