Spread the love“`html Understanding how to create a neural network can be a game-changer in the fields of artificial intelligence and machine learning. As industries increasingly rely on data-driven ...

Abstract: A fast gradient-descent (FGD) method is proposed for far-field pattern synthesis of large antenna arrays. Compared with conventional gradient-descent (GD) methods for pattern synthesis where ...

The first open-source implementation of Yau's Affine Normal Descent (YAND), a geometric optimization algorithm that derives search directions from the equi-affine normal of level-set hypersurfaces.

Abstract: Hybrid loss minimization algorithms in electrical drives combine the benefits of search-based and model-based approaches to deliver fast and robust dynamic responses. This article presents a ...

Every file in this project is code I wrote and submitted while completing the NeetCode ML course. The problems progressively build from gradient descent fundamentals all the way to a working GPT.

ABSTRACT: This paper proposes a symmetric alternating direction method of multipliers with two different relaxation factors for solving nonconvex optimization problems with linear constraints and a ...