Deep Learning with Yacine on MSN

How to implement stochastic gradient descent with momentum in Python

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning.
IEEE

SA-MARL: Novel Self-Attention-Based Multi-Agent Reinforcement Learning With Stochastic Gradient Descent

Abstract: In the rapidly advancing Reinforcement Learning (RL) field, Multi-Agent Reinforcement Learning (MARL) has emerged as a key player in solving complex real-world challenges. A pivotal ...
Learn With Jay on MSN

Mini-batch gradient descent in deep learning explained

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of ...
Scientific Research Publishing

Ruder, S. (2016) An Overview of Gradient Descent Optimization Algorithms. arXiv Preprint.

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 ...
IEEE

Learning Error Refinement in Stochastic Gradient Descent-Based Latent Factor Analysis via Diversified PID Controllers

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 ...
GitHub

Orthogonal Gradient Descent (OGD) for Continual Learning

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 ...
Frontiers

Leveraging pre-trained embeddings in an ensemble machine learning approach for Arabic sentiment analysis

1 Computer Science Department, Palestine Technical University - Kadoorie, Tulkarm, Palestine 2 Computer Science and Engineering Department, Universidad Carlos III de Madrid, Leganes, Spain ...
Frontiers

Reward-optimizing learning using stochastic release plasticity

Synaptic plasticity underlies adaptive learning in neural systems, offering a biologically plausible framework for reward-driven learning. However, a question remains ...
Microsoft

Stochastic Gradient Descent Tricks

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 ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

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 ...