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(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

  • Residual Sum of Squares