Matrix decomposition refers to the process of factorizing a matrix into a product of smaller matrices. By decomposing a large matrix, one can efficiently perform many matrix algorithms.

Common examples of matrix decompositions, each with its advantages and applications, include:

  • SVD
  • Spectral decomposition
  • LU decomposition
  • Cholesky
  • QR factorization
  • Schur decomposition
history | excerpt history