Negative Gradient and Gradient Descent Method

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Discussion Overview

The discussion centers on the concepts of "Negative Gradient" and "Gradient Descent Method," exploring their definitions, differences, relationships, and benefits. It touches on theoretical aspects of vector calculus and geometric interpretations.

Discussion Character

  • Conceptual clarification
  • Technical explanation
  • Debate/contested

Main Points Raised

  • Some participants inquire about the definitions and relationships between negative gradient and gradient descent method.
  • One participant asks for clarification on how to calculate the gradient of a function in vector calculus and its geometric meaning.
  • A later reply explains that the gradient vector indicates the direction of the steepest slope and that the negative gradient points downhill, suggesting its use in finding minimum values of a function.
  • Another participant expresses uncertainty about their mathematical skills and seeks assistance in understanding these concepts.

Areas of Agreement / Disagreement

Participants do not appear to reach a consensus on the definitions and applications of the negative gradient and gradient descent method, with some seeking clarification while others provide explanations.

Contextual Notes

There are limitations in the discussion regarding the depth of mathematical understanding among participants, as well as the reliance on external resources for foundational concepts.

Maria88
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What is "Negative Gradient" ? and what is "Gradient Descent Method" ? What is the difference and relationship between them ?
What is the benefit each of them ?
 
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Do you know how to calculate the gradient of a function, in vector calculus, and what it means geometrically?
 
jtbell said:
Do you know how to calculate the gradient of a function, in vector calculus, and what it means geometrically?
thanks a lot

No, I am not so good in math , I know this is a stupid question, but if you can answer it, I will appreciated that
 
You can find out how to calculate the gradient in any calculus textbook that includes multivariable calculus (vector calculus), and probably on hundreds of web sites including Wikipedia (http://en.wikipedia.org/wiki/Gradient), so I won't do that here. I'll just talk about the meaning of the gradient.

Suppose you have a function h(x,y) that tells you the elevation (height) of the land at horizontal coordinates (x,y). The gradient of this function, ##\vec \nabla h(x,y)##, is a vector function that gives you a vector for each point (x,y). This gradient vector points in the direction of steepest uphill slope, and its magnitude is the value of that slope (like the slope of a straight-line graph).

The opposite direction, the negative gradient ##-\vec \nabla h(x,y)## tells you the direction of steepest downhill slope.

If you want to find the location (x,y) at which h(x,y) is minimum (e.g. the bottom of a valley), one way is to follow the negative gradient vector downhill. Calculate ##-\vec \nabla h## at your starting point (x0, y0), take a step downhill in that direction to the point (x1, y1), calculate ##-\vec \nabla h## at that point, take a step in the new downhill direction, etc. Keep going until you find yourself at a higher elevation at the end of a step, indicating that you have gone past the bottom.

http://en.wikipedia.org/wiki/Gradient_descent
 

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