Function taking vectors of Rn as inputs

In summary, the conversation discusses the possibility of a function that takes vectors in Rn and returns a real value, with the dot product being an example. The function is referred to as a bilinear function or a function from R2n to R. The conversation also touches on using gradient descent to solve equations involving vectors and how to visualize the graph of such a function. The inspiration for this discussion is the mathematical treatment of calculating SVD, with a focus on finding the minimum of the equation, which is expected to be a paraboloid.
  • #1
gursimran
36
0
Hello friends,

Is it possible that a function take inputs as vectors in Rn and return one real value R. One such example is dot product. But keeping mathematical rigor in mind what should I call this function.

Problem 1.
Its a function from R2n to R
or
a function such that f(Rn,Rn)->R

Problem 2.
I want to solve this equation using gradient descent
|c - x.y|

here
c - scalar (R)
x and y are vectors in Rn

How should I visualize its graph?

This problem is inspired by the mathematical treatment used to calculated SVD here.

As proved by Ecart and young there could only be one minimum of the equation and the minimum should be SVD. So it means it should be a sort of parabolloid. How to visualize it.
 
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  • #2
gursimran said:
Hello friends,

Is it possible that a function take inputs as vectors in Rn and return one real value R. One such example is dot product. But keeping mathematical rigor in mind what should I call this function.

Problem 1.
Its a function from R2n to R
or
a function such that f(Rn,Rn)->R
If you want to consider it a bilinear function as usual, then it is the latter. If you are only interested in analytic properties, then you can use the former, but then we no longer have linearity.
Problem 2.
I want to solve this equation using gradient descent
|c - x.y|

here
c - scalar (R)
x and y are vectors in Rn
You can analytically consider ##\left| \sum_k (c_k - x_ky_k) \right|= n \circ \sum_k (c_k - x_ky_k)## and use the definition of your norm ##n##.
How should I visualize its graph?
The graph of a function ##f\, : \,\mathbb{R}^{2n} \longrightarrow \mathbb{R}## is an object in ##\mathbb{R}^{2n+1}##. This constraints visualizations to ##n = 1##. Probably not very informative but at least it displays the principle.
This problem is inspired by the mathematical treatment used to calculated SVD here.

As proved by Ecart and young there could only be one minimum of the equation and the minimum should be SVD. So it means it should be a sort of parabolloid. How to visualize it.
 

1. What is a vector in Rn?

A vector in Rn is a mathematical object that represents a directed line segment in n-dimensional space. It is typically denoted by a column of numbers enclosed in parentheses, such as (x1, x2, ..., xn).

2. How is a function defined for vectors in Rn?

A function that takes vectors in Rn as inputs is typically defined as follows: f: Rn → R, where n is the number of dimensions of the vector and R is the set of real numbers. This means that the function takes in a vector of n numbers and outputs a single real number.

3. Can a function take in multiple vectors in Rn as inputs?

Yes, a function can take in multiple vectors in Rn as inputs. For example, a function f: R3 → R could take in two vectors (x1, x2, x3) and (y1, y2, y3) as inputs and output a single real number.

4. What is the purpose of using vectors as inputs for a function?

Using vectors as inputs for a function allows us to generalize the function to operate on a larger set of data. It also allows us to perform operations on multiple variables at once, making calculations more efficient and concise.

5. How are functions that take vectors as inputs used in science?

Functions that take vectors as inputs are commonly used in many scientific fields, including physics, engineering, and computer science. They are used to model systems and phenomena that involve multiple variables, and to analyze data that is represented as vectors in n-dimensional space.

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