GitHub

This is a simple script for finding local minimum of a 2 argument function z=f(x,y) starting from given point (x,y).

There was an error while loading. Please reload this page. The gradient vector is a vector that points in the direction of the steepest increase of a function at a ...
GitHub

Gradient-Descent-and-Cost-Function-for-Test-Scores

This repository contains a Python implementation of the Gradient Descent algorithm, a fundamental optimization technique used in machine learning and data science. The code demonstrates how to use ...
Europe PMC

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses.

Despite the fact that the loss functions of deep neural networks are highly nonconvex, gradient-based optimization algorithms converge to approximately the same performance from many random initial ...
IEEE

An easy way to find gradient matrix of composite matricial functions

Abstract: A simple method to compute the gradient matrix of scalar-valued composite function of matrices is presented. Two examples are provided to show the efficiency of the approach.
IEEE

Quartic Gradient Descent for Tractable Radar Slow-Time Ambiguity Function Shaping

Abstract: We consider the problem of minimizing the disturbance power at the output of the matched filter in a single antenna cognitive radar set-up. The aforementioned disturbance power can be shown ...
Simon Fraser University

NLPNRA Call

See "Nonlinear Optimization and Related Subroutines" for a listing of all NLP subroutines. See Chapter 11, "Nonlinear Optimization Examples," for a description of the inputs to and outputs of all NLP ...