Stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates in applications involving large-scale data or streaming data. As an alternative version, averaged implicit SGD ...

(The Conversation is an independent and nonprofit source of news, analysis and commentary from academic experts.) Surprise: You can answer this question with modern algebra. Most folks who have been ...

Algebra often involves manipulating numbers or other objects using operations like addition and multiplication. Flavio Coelho/Moment via Getty Images You scrambled up a Rubik’s cube, and now you want ...

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 ...

Abstract: How to choose the step size of gradient descent method has been a popular subject of research. In this paper we propose a modified limited memory steepest descent method (MLMSD). In each ...

This program implements the Gaussian Elimination algorithm, a fundamental method in linear algebra for solving systems of linear equations, determining matrix inverses, and calculating determinants.

The current work aims at employing a gradient descent algorithm for optimizing the thrust of a flapping wing. An in-house solver has been employed, along with mesh movement methodologies to capture ...