Sparse principal component analysis for high dimensional multivariate time series

Mathematics

• Multivariate Time Series 100%
• Principal Component Analysis 82%
• High-dimensional 63%
• Principal Components 57%
• Social Media 46%
• Time series 46%
• Biomedical Imaging 44%
• Autoregressive Time Series 35%
• Financial Time Series 35%
• Spectral Norm 33%
• Mining 32%
• Nuisance Parameter 29%
• Transition Matrix 28%
• Dimensionality 26%
• Eigenvector 23%
• Covariance matrix 23%
• Angle 21%
• Rate of Convergence 19%
• Framework 14%

Engineering & Materials Science

• Principal component analysis 72%
• Time series 66%
• Eigenvalues and eigenfunctions 16%
• Covariance matrix 15%
• Imaging techniques 11%