Newton's Method for constrained optimization problems

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  • Опубликовано: 3 фев 2025

Комментарии • 10

  • @lorenzmichael7366
    @lorenzmichael7366 Год назад

    Super nice derivation of the matrix from Lagrange. Thank you!

  • @sujitm2727
    @sujitm2727 3 года назад +3

    Highly underrated

    • @tuongnguyen9391
      @tuongnguyen9391 2 года назад

      Why is it underated ? What make this video stand out ?

  • @beitexue2490
    @beitexue2490 2 года назад +1

    Clear explained
    👍

  • @AJ-et3vf
    @AJ-et3vf 2 года назад

    Great video. Thank you

  • @blxc1shcr10
    @blxc1shcr10 3 года назад

    h is linear or nonlinear?

    • @blxc1shcr10
      @blxc1shcr10 3 года назад

      It is explained at 8:00 but it's not very clear.

    • @matthewjames7513
      @matthewjames7513 3 года назад

      @@blxc1shcr10 nonlinear, but he makes a linear approximation for h

    • @englishvinglish3335
      @englishvinglish3335 2 года назад

      @@matthewjames7513 so can it be used for non linear ?

    • @matthewjames7513
      @matthewjames7513 2 года назад +1

      ​@@englishvinglish3335 This method is capable of solving a nonlinear optimization problem subject to nonlinear equality constraints. h(x) is a set of equality constraints. For example
      h1(x) = sqrt(x1*x2) = 0
      h2(x) = e^x1 = 0