Answer:
1,3 minimum
1,6 minimum
3,1 maximum
Step-by-step explanation:
Locate the h as x and the k as y for y-k=a(x-h)^2
Answer:
B just did the test
Step-by-step explanation:
9514 1404 393
Answer:
x +4y = -5
Step-by-step explanation:
The equation of the perpendicular line can be found by swapping the x- and y-coefficients and negating one of them. The new constant can be found by substituting the point values into the equation.
3x +12y = 3(-5) +12(0)
3x +12y = -15
We notice that all of the values include a factor of 3. We can divide that out to put the equation in standard form:
x + 4y = -5
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.
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The coffee shop used 52 pounds of Type A coffee.
Step-by-step explanation:
Cost of Type A coffee per pound = 5.25
Cost of Type B coffee per pound = 4.10
Total pounds used in blend = 142
Total cost = 642.00
Let,
x be the pounds of Type A coffee used
y be the pounds of Type B coffee used
According to given statement;
x+y=142 Eqn 1
5.25x+4.10y=642.00 Eqn 2
Multiplying Eqn 1 by 4.10

Subtracting Eqn 3 from Eqn 2

Dividing both sides by 1.15

The coffee shop used 52 pounds of Type A coffee.
Keywords: linear equation, elimination method
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