Answer:
1196 mm^2
Step-by-step explanation:
That's really well described. All in all you have 6 squares all laid out flat. Each square has a side of 14 mm.
The area of 1 square = 14mm * 14mm = 196 mm^2
The area of 6 squares = 6 * 196 mm^2 = 1176 mm^2
Answer:
Number line A.
Step-by-step explanation:
|-5x| - 11 = -1
Add 11 to both sides.
|-5x| = 10
-5x = 10 or -5x = -10
x = -2 or x = 2
Answer: Number line A.
Answer:
28m⁷n⁵
Step-by-step explanation:
You would first multiply 14 by 2. You would then multiply (which is really addition when it comes to exponents) your like-term exponents.
(14m²n⁵)(2m⁵) =28m⁷n⁵
14(2) = 28
m² + m⁵=m⁷
n⁵ + 0 = n⁵
The purpose of the tensor-on-tensor regression, which we examine, is to relate tensor responses to tensor covariates with a low Tucker rank parameter tensor/matrix without being aware of its intrinsic rank beforehand.
By examining the impact of rank over-parameterization, we suggest the Riemannian Gradient Descent (RGD) and Riemannian Gauss-Newton (RGN) methods to address the problem of unknown rank. By demonstrating that RGD and RGN, respectively, converge linearly and quadratically to a statistically optimal estimate in both rank correctly-parameterized and over-parameterized scenarios, we offer the first convergence guarantee for the generic tensor-on-tensor regression. According to our theory, Riemannian optimization techniques automatically adjust to over-parameterization without requiring implementation changes.
Learn more about tensor-on-tensor here
brainly.com/question/16382372
#SPJ4
Answer: The first queston you are just lining up the numbers
Step-by-step explanation:
