Conjugate gradient method
Método del gradiente conjugado
- Date
- 1952 · confidence high
- Place
- Los Angeles, California, United States
- Credited to
- Eduard Stiefel y Magnus Hestenes
- Field
- Knowledge & symbols
What it is
Iterative algorithm for solving systems of linear equations with symmetric positive-definite matrices, especially efficient for large sparse systems; developed by Hestenes and Stiefel at the Institute for Numerical Analysis.
What it led to
- numerical solution of partial differential equations
- large-scale optimization methods
- finite-element engineering simulations
- machine learning algorithms (conjugate gradient descent)