(Nonlinear) Optimization Library
This library aims to implement different mathematical optimization algorithms, such as regular and conjugate gradient descent. Mathematics is backed by Math.NET Numerics.
Gradient Descent Algorithms
- Resilient Error Gradient Descent
Conjugate Gradient Descent Algorithms
- Hager-Zhang ("CG_DESCENT")
- Polak-Ribière (supporting preconditioning)
- Fletcher-Reeves
Line Search Algorithms
- Secant
- Hager-Zhang with quadratic stepping
Cost Functions