Constrained Optimization: Intuition behind the Lagrangian

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  • เผยแพร่เมื่อ 28 ก.ย. 2024
  • This video introduces a really intuitive way to solve a constrained optimization problem using Lagrange multipliers. We can use them to find the minimum or maximum of a function, J(x), subject to the constraint C(x) = 0.
    - Want to see all of the references in a nice, organized list? Check out this journey on Resourcium: bit.ly/3KRxuOf
    - MATLAB Example: Problem-based constrained optimization: bit.ly/2Ll5wyk
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ความคิดเห็น • 33

  • @3d_chip
    @3d_chip หลายเดือนก่อน +2

    my god, two weeks of lectures explained in one video. you are great man.

  • @KHMakerD
    @KHMakerD ปีที่แล้ว +41

    “You’re not going to be solving it by hand.”
    *laughs then cries in graduate student*

  • @Joshjson
    @Joshjson 11 หลายเดือนก่อน +11

    Wish this was the way it was explained in university. Liked and subbed

  • @faraway27
    @faraway27 ปีที่แล้ว +5

    Thanks Brian, I always look forward to new Tech Talks! Could you do a video on MPC? That would be awesome!

    • @BrianBDouglas
      @BrianBDouglas ปีที่แล้ว +3

      I appreciate it! MathWorks already has a Tech Talk series on MPC so I doubt I'll make one in the near future. th-cam.com/play/PLn8PRpmsu08ozoeoXgxPSBKLyd4YEHww8.html. Perhaps one day when we revisit some of the older videos.

  • @vnagamohankrishnap1596
    @vnagamohankrishnap1596 ปีที่แล้ว +13

    You are a single piece, bro. You're explaining intuitions, makes me excited all the time.

  • @blower05
    @blower05 หลายเดือนก่อน

    I am confused about the slope obtained by differentiation. They are the slopes of dz/dx(i) but not the projection to the x-y plane. Thus, I cannot understand how it can be parallel?
    However, they are parallel if the "projections" slopes , ie. dx(2)/dx(1) is calculated and used. However, it is just 0 and were not used in the calculation.

  • @duydangdroid
    @duydangdroid 5 หลายเดือนก่อน +3

    had an undergrad professor so determined to stop cheaters that he only allowed scientific calculators which didn't bother me until he expected us to do regression

  • @SarahImeneKhelil
    @SarahImeneKhelil 8 หลายเดือนก่อน +3

    Brian, can you do for us a summer school course for control engineers I'll be the first one to attend if it's you talking about the intuition behind control!

  • @ryanfeng
    @ryanfeng ปีที่แล้ว +3

    Most inspiring video I ever seen. I got two takeaways: transferring none resolvable problem to an equivalent resolvable problem; gradient is a good way.

  • @kmishy
    @kmishy ปีที่แล้ว +3

    Great teaching❤

  • @Pedritox0953
    @Pedritox0953 ปีที่แล้ว +2

    Great video!

  • @AngeloYeo
    @AngeloYeo ปีที่แล้ว +3

    Great as always! 🎉

  • @user-dp9yn7zf4l
    @user-dp9yn7zf4l หลายเดือนก่อน

    5:45 the visual illusion make the dark line look curved .... XD

  • @harrytsai0420
    @harrytsai0420 ปีที่แล้ว +2

    Nice video! Looking forward to the nonlinear constrained optimization part!

    • @nitinjotwani69
      @nitinjotwani69 ปีที่แล้ว

      Hey, could you recommend any non linear constrained optimization videos?

  • @HeavenlyGodlyAngelic
    @HeavenlyGodlyAngelic 20 วันที่ผ่านมา

    I love this

  • @acc3095
    @acc3095 ปีที่แล้ว +1

    ❤❤❤❤❤ 🎉

  • @MrPepto93
    @MrPepto93 2 หลายเดือนก่อน

    I really have to learn to try ideas and equations with simple examples. I was so afraid Lagrange multipliers and Lagrange equation and its sense that I just dropped it off. How lucky that I just saw with the corner of my eye that thumbnail on my recommendation list with a characteristic Brianish drawing style with the "Lagrangian" word within the title. I knew before watching that you will help as always. Gosh you are a great educator man.

  • @razakawuni2138
    @razakawuni2138 3 วันที่ผ่านมา

    This is very helpful

    • @MATLAB
      @MATLAB  3 วันที่ผ่านมา

      Glad you like it!

  • @griffinbur1118
    @griffinbur1118 11 หลายเดือนก่อน +2

    Great video. In the interest of being precise and thinking about what might trip up new learners, someone who's paying really close attention will find 2:45 confusing since you can't have " *thee* partial derivative with respect to both x_1 and x_2". Instead, the gradient is a vector of all of the partial derivativeS, plural, of f( *x* ), where the ith element of the gradient is the partial derivative of f with respect to the ith element of *x*
    Sorry for the pedantry, but from my own experience, the problem is that we often ask math students to pay close attention to exactly that kind of fine distinction in other contexts, so a description of the gradient that, taken literally, can't exist is likely to cause minor confusion for talented students.
    That said, phenomenal video. This would be very useful for teaching someone who has only a knack for scalar calculus one of the most important ideas in multivariable calculus quite efficiently.

    • @BrianBDouglas
      @BrianBDouglas 11 หลายเดือนก่อน +1

      Thanks for the clarification. I appreciate hearing this type of feedback because it helps me change the way I present future videos. Cheers!

  • @DeepakRawat-t6s
    @DeepakRawat-t6s ปีที่แล้ว

    Can't see the video

    • @HansScharler
      @HansScharler ปีที่แล้ว

      It's working for me. What do you see?

    • @DeepakRawat-t6s
      @DeepakRawat-t6s ปีที่แล้ว

      @@HansScharler I just see a black screen

    • @BrianBDouglas
      @BrianBDouglas ปีที่แล้ว

      Did you get it figured out?

    • @MrPepto93
      @MrPepto93 2 หลายเดือนก่อน

      how do you type with eyes closed? :O