Answer:
First one is DC
Second one is AB.
Step-by-step explanation:
Just did them on edge.
Answer:
35
Step-by-step explanation:
If is given the value -8 as it is the input then -->
y = -4(-8) + 3
Negative four times negative 8 is positive 32 so
y= 32 + 3
And 32 plus 3 is 35
Answer:
150 feet
Step-by-step explanation:
the ratio of her shadow to her height
2/5=60/150
60/150=2/5
i hope it is right
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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It would be answer 4 because 14.85 divided by .05 is 297