IEEE

Low-Complexity Inverse Matrix Mini-Batch Gradient Descent for MIMO Equalization and Precoding

Abstract: As the size of base station antenna arrays continues to grow, even with linear processing algorithms, the computational complexity and power consumption required for massive MIMO ...
Hosted on MSN

Mini Batch Gradient Descent | Deep Learning | with Stochastic Gradient Descent

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

Forecast on the Productivity of a Multiple Effects Plan Solar Distiller ()

Laboratory of Matter, Environmental and Solar Energy Sciences (LASMES), UFR Sciences of the Structures of the Material and Technology, Félix Houphouët Boigny University, Abidjan, Côte d’Ivoire. In ...
marktechpost

This AI Paper Introduces Semantic Backpropagation and Gradient Descent: Advanced Methods for Optimizing Language-Based Agentic Systems

Language-based agentic systems represent a breakthrough in artificial intelligence, allowing for the automation of tasks such as question-answering, programming, and advanced problem-solving. These ...
marktechpost

Privacy Implications and Comparisons of Batch Sampling Methods in Differentially Private Stochastic Gradient Descent (DP-SGD)

Differentially Private Stochastic Gradient Descent (DP-SGD) is a key method for training machine learning models like neural networks while ensuring privacy. It modifies the standard gradient descent ...