Answer:
The salary after four consecutive increase = $ 46794.34
Step-by-step explanation:
According to question,
salary of MR. John = $ 40000 per year
percentage py increase = 4%
Let the salary after four consecutive pay increase = x
So, X = 40000 (1 +
)^4
Or, X = 40000 (
)^4
Or, X = 46794.34
Hence the salary increase after four consecutive pay increase at 4% = $46794.34 Answer
0.3 is 3 tenths.
The order of "ths" is tenths, hundredths, thousandths.
Since there are no numbers after the 3, you simply have to add 2 zeros to make it 300 thousandths.
0.300<span />
given:
she had: $35.13
+ her mom gave her: $7.50
+ she was paid $10.35
- add all of these up for total.
35.13 + 7.50 + 10.35
= $52.98
<em>look back at the answer i posted before for explanations. the answer for this would be 4/14, which is simplified to 2/7.</em>
<em />
Answer:
1.20%
Step-by-step explanation:
1.50-30=20
2.15000
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
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