Results 251 to 260 of about 13,377,918 (277)

Function Approximation

Deep Reinforcement Learning with Python, 2021
N. Sanghi
semanticscholar   +3 more sources

Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation

arXiv.org
Accurate approximation of complex nonlinear functions is a fundamental challenge across many scientific and engineering domains. Traditional neural network architectures, such as Multi-Layer Perceptrons (MLPs), often struggle to efficiently capture ...
SS Sidharth, R. Gokul
semanticscholar   +1 more source

Learning Function Approximators

1999
In this section we explain how it is possible to apply Machine Learning methods to acquire in an automatic way a control function out of a set of examples of execution of a task. The class of function approximators used, localized receptive field networks, is characterized and compared to other kinds of function approximators.
BAROGLIO, Cristina, GIORDANA, Attilio, Roberto Piola   +2 more
openaire   +2 more sources

Approximately Midconvex Functions

2008
Let X be a vector space and let D ⊂ X be a nonempty convex set. We say that a function f is δ-midconvex if $$ f\left( {\frac{{x + y}} {2}} \right) \leqslant \frac{{f(x) + f(y)}} {2} + \delta\;\;for x,y \in D. $$ We find the smallest function C : [0, 1] ∩ ℚ → ℝ such that for every δ-midconvex function f : D → ℝ the following estimate holds $$
Misztal, Krzysztof, Tabor, Jacek, Tabor, Józef   +2 more
openaire   +2 more sources

Approximately Multiplicative Functionals

Journal of the London Mathematical Society, 1986
Let \({\mathfrak A}\) be a commutative Banach algebra with dual \({\mathfrak A}^*\). For \(\phi \in A^*\), define \({\breve \phi}\)(a,b)\(=\phi (ab)- \phi (a)\phi (b)\), and call \(\phi\delta\)-multiplicative iff \(\| {\breve \phi}\| \leq \delta\). \({\mathfrak A}\) is an algebra in which approximately multiplicative functionals are near multiplicative
openaire   +1 more source

Universally Polygonally Approximable Functions

Journal of Applied Analysis, 2000
A function \(h:[0, 1]\to \mathbb{R}\) is said to be a polygonal function for \(f\) if there is a partition \(\{0= a_0 ...
Evans, M. J., Humke, P. D., O'Malley, R. J.   +2 more
openaire   +2 more sources

Approximations in Functional Analysis

Results in Mathematics, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lowen, Robert, Sioen, Mark
openaire   +3 more sources

Superfractal Approximation of Functions

Ukrainian Mathematical Journal, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Decomposition of Approximable Functions

The Annals of Mathematics, 1984
The purpose of this paper is to give a description of the space \(A_ D(F)\) of functions on a relatively closed subset F of an open plane set D which can be approximated uniformly on F by functions in H(D), i.e. functions analytic on D. The main result is the decomposition \[ A_ D(F)=C_{ua}(F\cup \Omega (F))+H(D)).
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Function Approximation

2008
Abstract We are given a certain amount of information about a function, f (x), in a specified interval, [a, b], and would like to sensibly approximate or represent the function with another simpler function, q(x), in the same interval.
openaire   +1 more source