Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning ...

Learn how backpropagation works using automatic differentiation in Python. Step-by-step implementation from scratch.

Introduction: Anxiety and depression are common among hypertensive patients and can lead to significant health complications. This study aimed to use Extreme Gradient Boosting (XGB) machine learning ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Scattering experiments using ultrashort X-ray free electron laser pulses have opened a ...

This repository contains source code for GLASS implemented with PyTorch. GLASS is a unified framework designed to enhance unsupervised anomaly detection by addressing the limitations in coverage and ...

Abstract: In this paper, we investigate reconfigurable intelligent surface (RIS)-assisted communication systems which involve a fixed-antenna base station (BS) and a mobile user (MU) that is equipped ...

ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...

ABSTRACT: In this paper, we investigate the convergence of the generalized Bregman alternating direction method of multipliers (ADMM) for solving nonconvex separable problems with linear constraints.