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Spring term

The main topics here are classical numerical methods to solve unconstrained and constrained optimization problems.

  1. Numerical optimization methods: introduction, convergence speed, classes of methods, black box model, one-dimensional optimization (ru Open In Colab, en Open In Colab)
  2. Unconstrained optimization problems
    • Gradient descent (ru, en)
    • Newton method (ru Open In Colab, en Open In Colab)
    • Conjugate gradient method (ru Open In Colab, en Open In Colab)
  • Least-squares problem (ru) Open In Colab, en Open In Colab)]
  1. Linear programming

    • Simplex method (ru Open In Colab, en Open In Colab)
    • Primal interior point method (ru Open In Colab, en Open In Colab)
  2. Constrained optimization problems

    • Projected gradient method and Frank-Wolfe method (ru, en)
    • Interior point methods (ru, en)
    • Penalty methods and augmented Lagrangian methods (ru, en)