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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 updating the weight parameters after assessing the entire dataset, Mini Batch ...
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 ...
Seeking Alpha

WiMi Studies Hybrid Quantum-Classical Convolutional Neural Network Model

BEIJING, Oct. 23, 2025 (GLOBE NEWSWIRE) -- BEIJING, Oct. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology ...
IEEE

An intelligent recommendation model for small batch gradient descent method

Abstract: In order to solve the problems of objective function oscillation and lack of accuracy caused by random gradient descent in intelligent recommendation system, a personalized recommendation ...
IEEE

Research on the Application of Gradient Descent Algorithm in Machine Learning

Abstract: The gradient descent algorithm is a type of optimization algorithm that is widely used to solve machine learning algorithm model parameters. Through continuous iteration, it obtains the ...
GitHub

gradient-descent-algorithm

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 ...