Eigenvalue and Generalized Eigenvalue Problems: Tutorial
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
Abstract
Open-access reader
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
Abstract
Open-access reader
This paper is a tutorial for eigenvalue and generalized eigenvalue problems. We first introduce eigenvalue problem, eigen-decomposition (spectral decomposition), and generalized eigenvalue problem. Then, we mention the optimization problems which yield to the eigenvalue and generalized eigenvalue problems. We also provide examples from machine learning, including principal component analysis, kernel supervised principal component analysis, and Fisher discriminant analysis, which result in eigenvalue and generalized eigenvalue problems. Finally, we introduce the solutions to both eigenvalue and generalized eigenvalue problems.
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This paper is a tutorial for eigenvalue and generalized eigenvalue problems. We first introduce eigenvalue problem, eigen-decomposition (spectral decomposition), and generalized eigenvalue problem. Then, we mention the optimization problems which yield to the eigenvalue and generalized eigenvalue problems. We also provide examples from machine learning, including principal component analysis, kernel supervised principal component analysis, and Fisher discriminant analysis, which result in eigenvalue and generalized eigenvalue problems. Finally, we introduce the solutions to both eigenvalue and generalized eigenvalue problems.
Key concepts: Divide-and-conquer eigenvalue algorithm, Eigenvalues and eigenvectors, Eigendecomposition of a matrix, Eigenvalue perturbation, Mathematics, Inverse iteration, Applied mathematics, Principal component analysis