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irina1246 [14]
3 years ago
5

The Inverse Function is one-to-one, find a formula for the inverse. (If anyone could explain how to find this mystical formula,

that would be great!)

Mathematics
1 answer:
S_A_V [24]3 years ago
7 0
Step 1. Substitute y for f(x) Step 2. Switch x and y. Step 3. Solve for y. Step 4. Substitute f(x) for y.

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Answer choices:<br>A (3 , -4)<br>B (4 , -7/2)<br>C (-5 , 8)<br>D (5/2 , -17/4)​
zhuklara [117]

Answer: D (5/2, -17/4)

Step-by-step explanation:  Using elimination your goal is to get rid or 1 variable  so you can solve for the one that's left.  By adding the -2y and 2y you will get 0.  You will also add the 3x+x (4x) and -1+11 (10).  You have now gotten rid of the y and have 4x=10.  By dividing each side by 4 we now know x =2.5.  D is the only possible solution with x=2.5 (5/2) but to solve for y you plug 2.5 in to an equation as x so) x-2y=11

                                                                           2.5-2y=11

                                                                            -2y=8.5                                                                        Answer D (5/2,-17/4)                                      y=-17/4 (4.25)

4 0
2 years ago
What is the answr to -5(b + 1) = 8
julsineya [31]

- 5(b + 1) = 8 \\  - 5b - 5 = 8 \\  - 5b = 8 + 5 \\  - 5b = 13 \\ b =  \frac{ - 13}{5}

PLEASE GIVE BRAINLIEST

8 0
2 years ago
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tensor-on-tensor regression: riemannian optimization, over-parameterization, statistical-computational gap and their interplay
Contact [7]

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

#SPJ4

7 0
2 years ago
The first table shows the teams with the four best records halfway through the season. The second table shows the full season re
Allisa [31]

Answer:

Step-by-step eThe first table shows the teams with the four best records halfway through the season. The second table shows the full season records for the same four teams. Which team had the best record during the second half of the season?

Record for the First Half of the Season Record for the Season

Teams Wins Loss Teams Wins Loss

1 26 14 1 59 21

2 27 13 2 27 13

3 25 15 3 25 15

4 24 16 4 24 16

Expert Answer

xplanation:

8 0
3 years ago
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List down 3 biotic and 3
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Examples of abiotic factors are water, air, soil, sunlight, and minerals. Biotic factors are living or once-living organisms in the ecosystem. These are obtained from the biosphere and are capable of reproduction. Examples of biotic factors are animals, birds, plants, fungi, and other similar organisms.
4 0
3 years ago
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