Answer:
44 because it goes into both of the numbers twice without going over
Step-by-step explanation:
Hope this helps and i am 100% sure it is correct if you are having doubts. Brainliest please
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
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Answer:

Step-by-step explanation:
we know that
The perimeter of triangle is equal to the sum of the length of the three sides
Let

the formula to calculate the distance between two points is equal to
Find the distance AB

substitute in the formula
Find the distance BC

substitute in the formula
Find the distance AC

substitute in the formula
Find the perimeter


Answer:
The diagonals of a square are perpendicular.
Step-by-step explanation: