Meaning of Lagrange multiplier

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  • Опубликовано: 22 янв 2025

Комментарии • 93

  • @8bit_pineapple
    @8bit_pineapple 6 лет назад +352

    lol, I went to 3Blue1Brown to see if Grant had any videos explaining what the langrange multipliar and lagrangians are.... seeing not I head over to Khan Academy... and Grant is teaching the lesson

    • @Jurgan6
      @Jurgan6 4 года назад +15

      Two years later, I did the exact same thing.

    • @brandontay2053
      @brandontay2053 4 года назад +8

      @@Jurgan6 2 months later, here I am, having done the same thing :')

    • @morancium
      @morancium 4 года назад +3

      @@brandontay2053 2 weeks later, mee too!!

    • @YashPatel-vt8or
      @YashPatel-vt8or 4 года назад +1

      me too

    • @morancium
      @morancium 4 года назад +1

      @@YashPatel-vt8or which college bro 😂

  • @sjwang3892
    @sjwang3892 3 года назад +51

    Went from Constrained Optimization Introduction to this video. Absolutely love the clear explanation w/ the graphs! No idea why other materials have to make it so hard to understand.

    • @technosapien330
      @technosapien330 11 месяцев назад +1

      My theory is they either don't actually understand the topic, or they are gate-keeping

  • @dirkjensen935
    @dirkjensen935 2 года назад +6

    Needed to pick up some basic know how about lagrangian in order to work through a proof regarding partition functions. And I was worried it was going to take me forever considering other texts I have aren't particularly clear and I didn't take lagrangian in undergrad. But oh my, this series is short, snappy, to the point and intuitive. Your tutorials are timeless and a gift to humanity. Thank you.

  • @masterchief8646
    @masterchief8646 4 года назад +15

    good Lord this video brought so much understanding to the LaGrange multiplier it´s insane. God bless you Sir

  • @leeris19
    @leeris19 6 месяцев назад +1

    Last time I checked I am studying how to minimize Optimum Margin Classifier for Support Vectors, now I am here, I don't know how, but I love it.

  • @mehdij9494
    @mehdij9494 6 лет назад +8

    I knew Lagrange Optimization since long time. But NOW I can claim understand it perfectly!
    Thank you so much!

  • @DefinitelyNotNhanTho
    @DefinitelyNotNhanTho 6 лет назад +45

    9:50 I believe what you meant was “let’s pause and ponder...” right ? Yeah, you can’t fool us, we know it was you lecturing, 3Blue1Brown.

  • @tunim4354
    @tunim4354 8 лет назад +25

    This is important in economics. One of the major concepts in Real business cycle.‎

    • @jairjuliocc
      @jairjuliocc 4 года назад +1

      I know im a little late but, Can you explain more?

    • @tunim4354
      @tunim4354 4 года назад +2

      @@jairjuliocc I was talking about the famous Real Business Cycle model in macroeconomics. When you are working with factors of production like labor and capital and you need Utility maximisation in a single period RBC model. The first order condition equations for capital and labor need a lagrange multiplier. If you are not a student of finance and economics, these will go over your head. And if you have studied macroeco, then these will be the most basic thing you learn.

    • @Leo-tf3rw
      @Leo-tf3rw 4 года назад +4

      @@tunim4354 wow you replied after 4 years

    • @hbbh
      @hbbh 3 года назад

      @@Leo-tf3rw AHAHHAHAH he did

    • @hbbh
      @hbbh 3 года назад

      That person probably already finished college

  • @pritomroy2465
    @pritomroy2465 4 года назад +6

    9:31 I thought most of the things in math comes from nowhere until I got your videos.

  • @phil97n
    @phil97n Год назад +1

    Many thanks! I learned about lagrange multipliers as of yesterday, but it's been rather difficult to understand just exactly what it is even thought the math makes sense - your video clarified for me. Thanks again

  • @vkoptchev
    @vkoptchev Месяц назад

    Nice. It would have been helpful if you had a link to the next video or the play list in the description.

  • @SuperIdiotMan00
    @SuperIdiotMan00 7 лет назад +57

    "Hours of Labor and Tons of Steel". That sounds like a rejected thrash metal album.

  • @ThePiMan0903
    @ThePiMan0903 2 года назад +2

    Thank you Khan Academy!

  • @rikenm
    @rikenm 8 лет назад +86

    It's a good refresher. Thanks. I would like to request you for advance math courses. You are very good at teaching. I watched your linear algebra playlist and also subscribed to your youtube (3Blue1Brown). It's awesome: How about abstract algebra, or even number theory. Thanks

    • @justinward3679
      @justinward3679 8 лет назад +8

      Riken Maharjan I second this!

    • @zes7215
      @zes7215 6 лет назад

      no such thing as gx or not

  • @alexanderherbertkurz
    @alexanderherbertkurz 7 лет назад +4

    thanks a lot, great video ... I watched a few videos on Lagrange multipliers and this is the best so far ... it would be great if there were links to the previous and next video in the series

  • @umountable
    @umountable 4 года назад +2

    how to find "the previous video" there is no playlist linked to the video

  • @Skandalos
    @Skandalos Год назад +1

    The voice sounds familiar. Is this the guy from the 3blue1brown channel? Anyway, this is very well explained.

  • @abdullaalmosalami
    @abdullaalmosalami 4 года назад +1

    Woah what! I was not expecting that lambda had some meaning! Oh why didn't my Calc 3 classes show me this. I don't even believe this was in my Calc 3 textbook, or maybe perhaps it was burried in some of the problems at the end of the Lagrange Multiplier section.

  • @dionsilverman4195
    @dionsilverman4195 5 лет назад +2

    How do we know that when the gradients are parallel, it's an extremum of the constraint g(x,y), rather than an inflection point? For example, extremising the paraboloid f(x,y) = x² +y² subject to y = 2x³ + 1. The gradients are parallel at (0,1), but this does not extremise the function f subject to the constraint g(x,y).
    Also, can I request a video on Lagrange multipliers with multiple constraints? This is much harder to find. I'm particularly interested in its use in deriving the Boltzmann distribution as maximising the number of micro states subject to constant molecule number and total energy. Also, a video on how this relates to Lagrangian or Hamiltonian mechanics would be fantastic and a common application I think.

  • @michaeljpchen6469
    @michaeljpchen6469 7 лет назад

    Really helpful to help me get a thorough understanding

  • @kawhiknot1016
    @kawhiknot1016 6 лет назад +1

    In what playlist does constraint programming topics it belongs?

  • @franks.6547
    @franks.6547 6 лет назад +1

    Wouldn't we suspect, just from looking at the parallel gradients of R and B, that for every small increase of B you get λ times an increase of R? I mean something like λ = |grad R|/|grad B| = dR/dB on a curve perpendicular to the two tangent contour lines -same as Anton Geraschenko says below, but more visually intuitive, I think. (I admit that you still have to believe that any variation of h and s should be along that perpendicular curve, but that is how you keep R and B contours tangent to each other)

  • @indranilroy691
    @indranilroy691 5 лет назад +1

    At 4:30, why we are taking gradient of L(Lagrangian function) = 0? Can anyone please put some light on this. Thanks!

    • @dsanjoy
      @dsanjoy 5 лет назад

      In a previous video it has been explained. You have to calculate the tangent of the two function and they have to be proportional to each other. The propionality constant is lambda.

  • @supreme84x
    @supreme84x 6 лет назад

    Wouldn't the contour of B be pointed down,, from the concavity? Or is the multiplier acting as a "negative" scalar, flipping it around?

  • @CalleTful
    @CalleTful 3 года назад

    Which playlist is this in?

  • @Rockyzach88
    @Rockyzach88 2 года назад

    So is the lagrange multiplier also considered an eigenvalue?

  • @xiaoweidu4667
    @xiaoweidu4667 4 года назад

    this is fantastic point !

  • @arslanhojiyev5996
    @arslanhojiyev5996 4 года назад

    If does not ask for the maximum ( or minimum), how can you know it is indeed the maximum (or minimum) value???

  • @liabraga4641
    @liabraga4641 7 лет назад +1

    So elucidating

  • @animeshpuzari8235
    @animeshpuzari8235 5 лет назад

    thanks😁🏅

  • @Uvenga
    @Uvenga 2 года назад +1

    The one who can not learn is because he doesn't want 💯

  • @miguelangelhernandezortiz7303
    @miguelangelhernandezortiz7303 2 года назад

    Anybody knows a book of Multivariable Calculus' history? Please help me.

  • @abhishek_sengupta
    @abhishek_sengupta 4 года назад

    wow...Thanx a lot!!

  • @RajatGoel1
    @RajatGoel1 6 лет назад +1

    6:47 REALLY!!!

  • @atriagotler
    @atriagotler 3 года назад

    I love you grant.

  • @johncharles3907
    @johncharles3907 4 года назад

    I think I need some more animations to understand this.

  • @usamsersultanov689
    @usamsersultanov689 7 лет назад

    Finally I got it

  • @elgodyr2683
    @elgodyr2683 3 года назад

    guys can the lamda be equal to 0 ?

    • @goclbert
      @goclbert 2 года назад

      Yeah but wouldn't that just mean our constraint has no impact on our ability to optimize R?

  • @Majestic469
    @Majestic469 5 лет назад

    Why can’t you just solve for h or s in one function and substitute that expression in the other function? Then you can just set the derivative to 0 to find the optimization.

    • @MayankGoel447
      @MayankGoel447 2 года назад

      That's not always possible. If say, your constraint function was not factorizable e.g. xsin(y) + yx^2=1. In this case, you can't express x in terms of y or the other way around and substitute that in f(x)

  • @sam4395
    @sam4395 8 лет назад +4

    oh

  • @Postermaestro
    @Postermaestro 7 лет назад

    Commenting to spread on the tubes!

  • @dagia3209
    @dagia3209 5 лет назад

    I like it

  • @anas.2k866
    @anas.2k866 4 года назад

    I don't see why the two fradient are propotinal

    • @hectorbetancourt2854
      @hectorbetancourt2854 4 года назад

      Because you made them so through the Lagrange multiplier. There are multiple grads of the contour of the function that don't have a proportional grad with the constraint, but by assuming that they are (and that they relate to each other through the Lagrande multiplier), you can solve the system of equations and get all the points at which your previous assumption, that the two gradients are proportional, is true.

  • @buh357
    @buh357 3 года назад

    F**k, This is GOLD.

  • @mv2g09
    @mv2g09 Год назад

  • @tag_of_frank
    @tag_of_frank 4 года назад

    Argh why no inequality constraints

  • @jullevv
    @jullevv 8 лет назад +1

    first like

  • @theacademyofgermanidealism6210
    @theacademyofgermanidealism6210 4 года назад

    3blue one brown guy

  • @tadasvaitkevicius5799
    @tadasvaitkevicius5799 5 лет назад

    i dont like that he speaks so fast

  • @Jmtri7
    @Jmtri7 4 года назад

    While you maximize your revenue, I'll be maximizing my profit... ;)

  • @alaypal7484
    @alaypal7484 6 лет назад

    Omg

  • @shellycollorone3703
    @shellycollorone3703 8 лет назад +1

    why sending math i'm not needing ?

    • @zayedalsuwaidi7697
      @zayedalsuwaidi7697 8 лет назад +3

      Maybe just don't click videos you do not need to see?

    • @shellycollorone3703
      @shellycollorone3703 8 лет назад +1

      iii 3xki they sending a different kind of math i don't need.

    • @zayedalsuwaidi7697
      @zayedalsuwaidi7697 8 лет назад +2

      Shaelyne Collorone
      Okay, I understand this. But why don't you just go on the website www.khanacademy.com and look for what you need instead of clicking on videos you don't want to see?

    • @edjrage7745
      @edjrage7745 4 года назад

      @@shellycollorone3703 who is they