Step-by-step explanation:
(2m + 4) / 8 = w
2m + 4 = 8w
2m = 8w - 4
m = 4w - 2
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:
Mr. Mole is descending by 2.4 meters per minute
Step-by-step explanation:
Let
x ----> the time in minutes
y ---> the distance in meters
we know that
In this problem the rate of change or slope is the same that the speed
The formula to calculate the slope between two points is equal to

take two points from the table
(5,-18) and (8,-25.2)
substitute the values in the formula

---> is negative because is descending
A. The reduction in Angela’s tips are cause by low restaurant sales. Even tho shes still getting her 20% it’s less money due to the fact they’re less customers
The expression xy-2, when x=3 and y= -4, becomes (3)(-4)-2, or -14 (answer)
the expresion 3x^2*y - 4 becomes 3(3)^2*(-4) - 4, or 27(-4) - 4, or -108 - 4 = -112 (answer)
Leave Timmy out of this, since it seems he didn't really do anything. ;)