An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...

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 ...

This repository explores the concept of Orthogonal Gradient Descent (OGD) as a method to mitigate catastrophic forgetting in deep neural networks during continual learning scenarios. Catastrophic ...

Amplifying words and ideas to separate the ordinary from the extraordinary, making the mundane majestic. Amplifying words and ideas to separate the ordinary from the ...

Re “Throwaway Plastic Has Corrupted Us,” by Saabira Chaudhuri (Opinion guest essay, Sept. 7): Ms. Chaudhuri is right when she writes: “Single-use plastic was never inevitable. It was a business ...

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 ...

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 ...

Each algorithm and line search combination is tested on 12 different optimization problems. Plots for each problem will be saved in the figures directory. Data for each problem will be saved in the ...