Body: <p>As in <a href="https://en.wikipedia.org/wiki/Calculus_of_variations" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Calculus_of_variations</a></p>
  
  <blockquote>
    <p>The calculus of variations is a field of mathematical analysis that
    uses variations, which are small changes in functions and functionals,
    to find maxima and minima of functionals</p>
  </blockquote>
  
  <p>The Gradient Descent algorithm is also a method to find minima of a function, it it a part of the Calculus of Variations?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-04T11:34:45.123Z
Comments.Text: How is this question related to AI? You should at least mention where variational calculus can be used in AI. I know where it can be used, but you should edit your post to make this question more on-topic.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-04T17:32:19.343Z
Comments.Text: Gradient Descent is AI, and the confusing term here is 'finding minima'
Comments.UserDisplayName: Dan D.
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-04T22:59:49.463Z
Comments.Text: @datdinhquoc GD alone is not AI. GD is an iterative optimization algorithm, which can also be used in other contexts that someone would not necessarily call AI. I will help you. You could say something like "GD is used to train neural networks and variational calculus is used in computer vision" as a premise, then ask your question.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-02-05T03:15:05.800Z
Comments.Text: it's maths, yes, but it's used in AI as the basic optimiser
Comments.UserDisplayName: Dan D.
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-09-25T01:59:33.957Z
Comments.Text: @datdinhquoc ok. but this is related with Directional Derivatives and the Gradient Vector, max and min values from Calculus? anyone can confirm?
Comments.UserDisplayName: rubengavidia0x
Tags: <machine-learning><gradient-descent><variational-autoencoder><calculus><math>
Title: Is Gradient Descent algorithm a part of Calculus of Variations?
UserDisplayName: Dan D.
ThreadText: # Is Gradient Descent algorithm a part of Calculus of Variations?
  
  (Asked by: username_0 on 2020-02-04)
  
  As in <https://en.wikipedia.org/wiki/Calculus_of_variations>
  
  > The calculus of variations is a field of mathematical analysis that
  > uses variations, which are small changes in functions and functionals,
  > to find maxima and minima of functionals
  
  The Gradient Descent algorithm is also a method to find minima of a function, it it a part of the Calculus of Variations?
  
  **Tags:** machine-learning, gradient-descent, variational-autoencoder, calculus, math
  
  > **Comments:**
  > **username_1**: How is this question related to AI? You should at least mention where variational calculus can be used in AI. I know where it can be used, but you should edit your post to make this question more on-topic.  
  > **username_0**: Gradient Descent is AI, and the confusing term here is 'finding minima'  
  > **username_1**: @datdinhquoc GD alone is not AI. GD is an iterative optimization algorithm, which can also be used in other contexts that someone would not necessarily call AI. I will help you. You could say something like "GD is used to train neural networks and variational calculus is used in computer vision" as a premise, then ask your question.  
  > **username_0**: it's maths, yes, but it's used in AI as the basic optimiser  
  > **username_2**: @datdinhquoc ok. but this is related with Directional Derivatives and the Gradient Vector, max and min values from Calculus? anyone can confirm?  
  
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  ## 0 answers
  
  