The tag has no wiki summary.

learn more… | top users | synonyms

12
votes
1answer
303 views

Why was Schönfinkel's work on eliminating “bound variables” in logic so crucial?

AFAIK, The first evidence of using higher order functions goes back to Schönfinkel's 1924 paper: "On the Building Blocks of Mathematical Logic" - where he allowed one to pass functions as ...
3
votes
1answer
91 views

Constructing terms of function types out of the empty type

If a function $f$ is understood as its graph, i.e. a set of pairs $\langle x,y\rangle$ where $x$ is input and $y$ is output, then the empty set $\emptyset$ is a valid function, and for any set $A$, we ...
0
votes
1answer
190 views

Newbie question: Meta-functions?

Consider a function F that takes a function and produces a function based on structure of the input function. As an example consider F that takes all functions having at least two conditionals and ...
8
votes
0answers
109 views

Can polynomial-sized circuits use garbage?

This is a non-uniform (and simplified) version of my previous question about Cook reductions. Let $R\subseteq \{0,1\}^*\times\{0,1\}$. A function $r\colon \{0,1\}^*\to\{0,1\}$ solves $R$ if ...
3
votes
1answer
151 views

Cook reduction for search problems, by universal property?

A search problem is a relation $R\subseteq \Sigma^*\times\Sigma^*$. A function $f\colon \Sigma^*\to\Sigma^*$ solves $R$ if $(x,f(x))\in R$ for all $x\in\Sigma^*$. Define a search problem to be ...
19
votes
1answer
648 views

Programming languages with canonical functions

Are there any (functional?) programming languages where all functions have a canonical form? That is, any two functions that return the same values for all set of input is represented in the same way, ...
6
votes
1answer
133 views

Combining (block)-sensitivity and Lipschitz conditions?

If we're given a boolean function $f : \{0,1\}^n \rightarrow \{0,1\}$, we can define its sensitivity as follows. The sensitivity $s(f, w)$ with respect to input $w$ is the number of ways of flipping a ...
7
votes
1answer
1k views

Universal Function approximation

It is known via the universal approximation theorem that a neural network with even a single hidden layer and an arbitrary activation function can approximate any continuous function. What other ...