Independent component analysis for tensor-valued data
From MaRDI portal
Publication:1679572
DOI10.1016/j.jmva.2017.09.008zbMath1381.62107arXiv1602.00879OpenAlexW2269587443WikidataQ109772906 ScholiaQ109772906MaRDI QIDQ1679572
Publication date: 9 November 2017
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1602.00879
Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20)
Related Items (7)
Tensor Canonical Correlation Analysis With Convergence and Statistical Guarantees ⋮ Independent component analysis for tensor-valued data ⋮ Independent component analysis for multivariate functional data ⋮ Projected estimation for large-dimensional matrix factor models ⋮ JADE for Tensor-Valued Observations ⋮ On the usage of joint diagonalization in multivariate statistics ⋮ Application of the sequential matrix diagonalization algorithm to high-dimensional functional MRI data
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Invariant Co-Ordinate Selection
- Tensor Decompositions and Applications
- Fourth moments and independent component analysis
- Tensor sliced inverse regression
- Characteristics of multivariate distributions and the invariant coordinate system
- The multilinear normal distribution: introduction and some basic properties
- A survey of multilinear subspace learning for tensor data
- Models with a Kronecker product covariance structure: estimation and testing
- Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure
- Eigenvectors of a kurtosis matrix as interesting directions to reveal cluster structure
- Squared skewness minus kurtosis bounded by 186/125 for unimodal distributions
- Independent component analysis for tensor-valued data
- Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion
- On dimension folding of matrix- or array-valued statistical objects
- On multilinear principal component analysis of order-two tensors
- Tests for Kronecker envelope models in multilinear principal components analysis
- Statistical Analysis of Financial Data in S-Plus
- Sliced Inverse Regression for Dimension Reduction
- A Multilinear Singular Value Decomposition
- On Estimation of Covariance Matrices With Kronecker Product Structure
- Geodesic Convexity and Covariance Estimation
- Deflation-Based FastICA With Adaptive Choices of Nonlinearities
- Robust Kronecker Product PCA for Spatio-Temporal Covariance Estimation
- Advanced Linear Algebra
- Regularized Matrix Regression
- Tensor Regression with Applications in Neuroimaging Data Analysis
- On Invariant Coordinate System (ICS) Functionals
- Dimension folding PCA and PFC for matrix-valued predictors
- Structured lasso for regression with matrix covariates
This page was built for publication: Independent component analysis for tensor-valued data
