PyTorch optimizer based on nonlinear conjugate gradient method
A matlab function for steepest descent optimization using Quasi Newton's method : BGFS & DFP
Repository for machine learning problems implemented in python
Bespoke, from scratch, implementation of Armijo-Wolfe inexact line search technique to find step length for gradient descent optimisation. The library alternative is scipy.optimize.line_search
Assignments for Optimization Techniques Course at ECE AUTH. Includes Steepest Descent, Levenberg-Marquardt and a Genetic Algorithm implementation for Network Traffic Optimization.
Comparison of Gradient Descent and Block Coordinate Gradient Descent methods through a semi supervised learning problem.
Python implementations of classical nonlinear optimization methods, including Newton, steepest descent, conjugate gradient, and Armijo line search.
Gradient Descent Lab: Methods and Empirical Behavior
This project is about the implementation of unconstrained optimization algorithms
[Optimization Algorithms] Implementation of Nonlinear least square curve fitting using the Gauss-Newton method and Armijio’s line search.
Implementation of Trust Region and Gradient Descent methods for Multinomial Regression
This repository contains an implementation of the Gradient Descent Algorithm in C++, utilizing the Armijo condition to optimize step sizes.
some option technics within python and R
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