The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...

The YOLOv8 and Swin Transformer dual-module system significantly improves structural crack detection, offering a faster and more accurate inspection method.

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning. Mike Johnson gives update on Jan. 6 plaque Alaska received 7 feet of snow, sinking ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

The first chapter of Neural Networks, Tricks of the Trade strongly advocates the stochastic back-propagation method to train neural networks. This is in fact an instance of a more general technique ...

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 ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...

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 ...

Abstract: In Big Data-based applications, high-dimensional and incomplete (HDI) data are frequently used to represent the complicated interactions among numerous nodes. A stochastic gradient descent ...

Abstract: Phase control is paramount for laser beam combination, requiring sequential tip/tilt and piston error correction. The common stochastic parallel gradient ...