[nisuni]

You are nitpicking, and completely missing my point. Let me rephrase it.

The original article is about neural networks being able to represent any function (for some definition of any).

I was just pointing out that there exists much cheaper ways of representing any function. Therefore the article seems very unexciting to me.

Btw, you have chose L^2(R) yourself and then used that to show that there are interesting function not in the space you have chosen, quite a circular argument.

Since the article on neural networks never mentions functions defined on a infinite domain, one can easily take L^2([0,1]) or L^2([0,Lambda]) up to some cutoff Lambda. I would say that all non-pathological functions you can think of are there!

[dragon96]

> You are nitpicking, and completely missing my point.

> I was just pointing out that there exists much cheaper ways of representing any function. Therefore the article seems very unexciting to me.

To be fair, your original comment didn't really make a point. What kind of cheaper representations do you have in mind? What makes an orthogonal basis of functions too "expensive" a representation for your taste?

> I would say that all non-pathological functions you can think of are there!

I'd argue that most "real functions" that we care to learn (e.g. mappings between high dimensional data and labels) are pathological. In this sense, we should really care about the completeness of these spaces, perhaps even more than the well-behaved ones.

[nisuni]

Most functions are pathological? Are you serious?

All physics assumes you are dealing with non-pathological functions, except for some really particular cases. You can do nearly everything in Electromagnetism and nearly all Quantum Mechanics with non pathological functions.

Maybe we have a different definition of pathological, I am using it in the way a physicist would use (i.e. continuous, continuous derivatives, so on)

[dragon96]

The physics I've done have only done with n-particle systems, where n is a number I can count on a hand. Likewise, most of the examples I'd learn in a pure math class are either (a) relatively well-behaved objects with nice properties or (b) "pathological" objects that are constructed specifically to prove a counterpoint.

The kind of pathological function that I'm referring to is neither of these. For example, what does the manifold of all 1 second clips of the word "the" look like? If the clip is sampled at 60 Hz, each clip is already in 60d space. I'm inclined to think that it's some unimaginably complicated manifold that would likely fall into the category of "edge cases", which previous commenters have mentioned and it sounds like you're discounting as nitpicking.

I don't know if this aligns with what you mean by a pathological function, and I'm happy to continue having this discussion with a more concrete example of what you mean. :)