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Linear regression using gradient descent explained simply

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...
IEEE

A Mirror Descent-Based Algorithm for Corruption-Tolerant Distributed Gradient Descent

Abstract: Distributed gradient descent algorithms have come to the fore in modern machine learning, especially in parallelizing the handling of large datasets that are distributed across several ...
Scientific Research Publishing

Fox, J. (2015) Applied Regression Analysis and Generalized Linear Models, Third Edition. SAGE Publications, Inc.

ABSTRACT: This study presents the Dynamic Multi-Objective Uncapacitated Facility Location Problem (DMUFLP) model, a novel and forward-thinking approach designed to enhance facility location decisions ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
GitHub

luherod/Algebra_-_Linear_regression_-_Gradient_descent

This project explores linear regression using both the least squares method and gradient descent. It implements the matrix form of linear regression and applies it to a real-world dataset. The ...
IEEE

A Hybrid Gradient Algorithm for Linear Regression with Hybrid Signals

Abstract: Given a linear input/output relationship involving unknown parameters, we propose a hybrid gradient descent algorithm to estimate the unknown parameters when the inputs and the outputs are ...