Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
AlphaGalileo

PLSaoNET: A Clear Path for Industrial Network Training, Away from Random Initialization

A research team from the Chinese Academy of Sciences proposed PLSaoNET, a general method that provides neural networks a statistically meaningful ...
Frontiers

Gradient Decomposition Methods for Training Neural Networks With Non-ideal Synaptic Devices

As artificial intelligence (AI) applications become ubiquitous in medical care, autonomous driving, robotics, and other fields, accuracy requirements and neural network complexity increase in tandem, ...
IEEE

A Batch Variable Learning Rate Gradient Descent Algorithm With the Smoothing

Abstract: A batch variable learning rate gradient descent algorithm is proposed to efficiently train a neuro-fuzzy network of zero-order Takagi-Sugeno inference systems. By using the advantages of ...
IEEE

Aero-Engine On-Board Model Based on Batch Normalize Deep Neural Network

Abstract: A new on-board turbo-fan engine modeling method based on a batch normalize (BN) mini-batch gradient descent (MGD) deep neural network (NN) is proposed. This new method adopts BN algorithm, ...