4 5/6 would be your answer then you figure out how to take away the whole number
Answer:
a.) x = 5.36
b.) y = - 0.001
c.) t = 11.26
d.) k = 4.57
Step-by-step explanation:
a) x−1.27=4.09
b) 2.3−y=2.301
c) t+3.04=14.3
d) 1.1+k=5.67
Solving. right?
a.) x = 4.09 + 1.27 = 5.36
b.) y = 2.3 - 2.301 = - 0.001
c.) t = 14.3 - 3.04 = 11.26
d.) k = 5.67 - 1.1 = 4.57
The correct answer for this problem is 6,500 in one month
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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Quotient=19
remainder= 3
or
mixed number = 3/35
