Numerator of the equation is 3*nDenominator is 4*p - 5*n The equation is m = 3n/(4p-5n)
Numerator = 3*n
Denominator = 4*p - 5*n
Equation = [m = 3n/(4p-5n)]
The correct answer for this would be 32/5
Y=mx+b
lines are parallels so m=2
y=2x+b
line passing through the point (4,2), so x=4 y=2
put these value in equation
2=2*4+b
2=8+b
b=2-8
b=-6
y=2x-6
Answer: y=2x-6
(verification on the picture)
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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Yes, because it does not matter which order you multiply the factors in; you will always get the same answer.
