User:Programminglinguist/Books/Useful Matrix Theory
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Useful Matrix Theory
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- Affine space
- Affine transformation
- Basis (linear algebra)
- Broyden–Fletcher–Goldfarb–Shanno algorithm
- Cayley–Hamilton theorem
- Change of basis
- Cholesky decomposition
- Conjugate gradient method
- Conjugate transpose
- Convex function
- Convex optimization
- Determinant
- Dual space
- Eigenvalues and eigenvectors
- Galilean transformation
- Gradient descent
- Haynsworth inertia additivity formula
- Hessenberg matrix
- Hessian matrix
- Higher-order singular value decomposition
- Householder transformation
- Householder's method
- Inner product space
- Jacobian matrix and determinant
- Lagrange multiplier
- Least squares
- Line search
- Linear least squares (mathematics)
- Linear map
- Lipschitz continuity
- Lorentz transformation
- LU decomposition
- Matrix congruence
- Matrix consimilarity
- Matrix similarity
- Minor (linear algebra)
- Moore–Penrose pseudoinverse
- Newton's method
- Newton's method in optimization
- Nonlinear programming
- Norm (mathematics)
- Normed vector space
- Nullity theorem
- Orthogonal matrix
- Orthonormality
- Polar decomposition
- Preconditioner
- QR decomposition
- Rank–nullity theorem
- Schur complement
- Schur decomposition
- Shear mapping
- Singular value decomposition
- Spectral theorem
- Squeeze mapping
- Stochastic gradient descent
- Topological vector space
- Transformation matrix
- Tridiagonal matrix
- Woodbury matrix identity