Function approximation, a central theme in numerical analysis and applied mathematics, seeks to represent complex functions through simpler or more computationally tractable forms. In this context, ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs ...

UCLA researchers demonstrate diffractive optical processors as universal nonlinear function approximators using linear ...

The purpose of this note is to establish a natural connection between the minimizers of two closely related variational problems. We prove global and local convergence results for the p-harmonic ...

Mathematics of Computation, Vol. 84, No. 294 (JULY 2015), pp. 1835-1860 (26 pages) The Padé approximation has a long and rich history of theory and application and is known to produce excellent local ...

Can light perform millions of calculations at once without extra materials? A new optical system shows how this can be done.

Statistical Approximation Theory and Operators is a vibrant area within applied mathematics that investigates how diverse families of operators can be utilised to ...

This paper develops a new scheme for improving an approximation method of a probability density function, which is inspired by the idea in the Hilbert space projection theorem. Moreover, we apply ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear ...

In their 2001 paper, Longstaff and Schwartz suggested a method for American option pricing using simulation and regression, and since then this method has rapidly gained importance. However, the idea ...