Find the dimension that counts: Fast dimension estimation and Krylov PCA

Computer Science

• Covariance Matrix 100%
• Principal Component 100%
• Component Analysis 100%
• Application 66%
• Approximation (Algorithm) 66%
• Models 33%
• Data Analysis 33%
• Computing 33%
• Signal Processing 33%
• Algorithms 33%
• High Dimensional Data 33%
• Machine Learning 33%
• Data Application 33%
• Krylov Subspace Method 33%
• Dimensional System 33%
• Image Processing 33%
• Selection Criterion 33%
• Analysis Signal 33%
• Sample Covariance Matrix 33%

Mathematics

• Subspace 100%
• PCA 100%
• Covariance Matrix 60%
• Approximation 40%
• Number 20%
• Dimensional Data 20%
• Selection 20%
• Random Matrix 20%
• Complete 20%
• Image Processing 20%
• Algorithm 20%
• Data Point 20%
• Numerical Experiment 20%
• Perturbation Theory 20%
• Degrees of Freedom 20%
• Sample Covariance Matrix 20%
• Dimensional System 20%
• Model Selection 20%
• Signal Processing 20%