Abstract: In this paper, a novel variable order fractional gradient descent optimization algorithm is proposed, which generalizes the classical gradient descent method by introducing a kind of ...

Abstract: The main difficulty in using artificial neural networks, which are designed for classification, to detect a rare subpixel target in hyperspectral imaging is that there is typically only one ...

The objective of this notebook is to compare the methodologies used in linear regression: traditional statistical techniques versus machine learning optimization methods, such as gradient descent.

SIAM Journal on Numerical Analysis, Vol. 15, No. 6 (Dec., 1978), pp. 1247-1257 (11 pages) This paper studies the convergence of a conjugate gradient algorithm proposed in a recent paper by Shanno. It ...

A new mixed variational formulation for the Navier-Stokes equations with constant density and variable viscosity depending nonlinearly on the gradient of velocity, is proposed and analyzed here. Our ...