In this study, we focus on investigating a nonsmooth convex optimization problem involving the l 1-norm under a non-negative constraint, with the goal of developing an inverse-problem solver for image ...

Your browser does not support the audio element. The backpropagation algorithm is the cornerstone of modern artificial intelligence. Its significance goes far beyond ...

From a neuroscience perspective, artificial neural networks are regarded as abstract models of biological neurons, yet they rely on biologically implausible backpropagation for training. Energy-based ...

Abstract: To improve the estimation accuracy of the state of charge (SOC) in power batteries for electric vehicles, this study proposes a novel modeling and online SOC estimation method using Back ...

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners! Parkinson’s Isn’t Just Bad Luck. Scientists Reveal It’s Largely Preventable—and the Culprit Is All ...

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 ...

This file explores the working of various Gradient Descent Algorithms to reach a solution. Algorithms used are: Batch Gradient Descent, Mini Batch Gradient Descent, and Stochastic Gradient Descent ...