Sign confusion when taking gradient (Newton's Method)

Click For Summary
SUMMARY

The discussion centers on the application of Newton's Method in n-dimensional optimization, specifically addressing the confusion regarding the sign of the gradient. The function in question is g(x,y) = 1 - (x-1)^4 - (y-1)^4, with a local maximum at (1,1). The gradient is correctly calculated as F(x,y) = [4(x-1)^3, 4(y-1)^3] transpose, rather than using a negative sign. This is due to the convention that the gradient points in the direction of steepest ascent, which is essential for the optimization process.

PREREQUISITES
  • Understanding of Newton's Method for optimization
  • Familiarity with gradient and Hessian matrix concepts
  • Knowledge of multivariable calculus
  • Experience with critical points in functions of multiple variables
NEXT STEPS
  • Study the derivation of gradients in multivariable functions
  • Learn about the Hessian matrix and its role in optimization
  • Explore the implications of local maxima and minima in n-dimensional spaces
  • Investigate numerical methods for optimization beyond Newton's Method
USEFUL FOR

Students and professionals in mathematics, data science, and engineering who are working with optimization techniques in multivariable calculus, particularly those utilizing Newton's Method for finding critical points.

zmalone
Messages
10
Reaction score
0
I'm watching a lecture on Newton's method with n-dimensions but I am kind of hung up on why the professor did not use the negative sign while taking the first gradient? Is there a rule that explains this or something that I'm forgetting? The rest makes sense but highlighted in red is the part I am confused on if anyone can clear that up I'd appreciate it, thanks!

Where g(x,y) = 1-(x-1)^4-(y-1)^4

local maximum at (1,1) ; critical point at (1,1)

Gradient of g(x,y):

F(x,y,) = [Dg(x,y,)]transpose = [4(x-1)^3 4(y-1)^3]transpose
Why not [-4(x-1)^3 -4(y-1)^3]?

Gradient of F(x,y):

DF(x,y) =
12(x-1)^2 0
0 12(y-1)^2

Screen shot which is probably easier to read:
 

Attachments

  • NewtonMethodQuestion.jpg
    NewtonMethodQuestion.jpg
    13.3 KB · Views: 445
Physics news on Phys.org
The gradient in Cartesian components is, of course, given by
\vec{\nabla} g=(\partial_x g,\partial_y g)=(-4(x-1)^3,-4 (y-1)^3)
and the Hesse Matrix by
H_{ij}=\partial_i \partial_j g=\mathrm{diag}(-2(x-1)^2,-12(y-1)^2).
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 13 ·
Replies
13
Views
3K
  • · Replies 18 ·
Replies
18
Views
3K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 6 ·
Replies
6
Views
4K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 14 ·
Replies
14
Views
2K