程序代写代做代考 algorithm PowerPoint Presentation

PowerPoint Presentation

Lecture 5: Gradient Descent

Basic algorithm for gradient descent:

BASIC-GRADIENT-DESCENT(f)
i = 0
x0 = arbitrary point
while f′(xi) !≈ 0 do
if f′(xi) > 0 : move left
if f′(xi) < 0 : move right i = i + 1 if f′(xi) ≈ 0 then x is a local extremum f′(xi) ≈ 0 is local optimality condition. Gradient Descent: Tangent lines (red) of f at successive points xi (green) (MathWorks image) Nonconvex objective function: different starting points can give different local minima. Convex function on an interval. /docProps/thumbnail.jpeg