InfoWorld

Gradient descent in Java

Find out why backpropagation and gradient descent are key to prediction in machine learning, then get started with training a simple neural network using gradient descent and Java code. Most ...

How Do Machine Learning Models Learn? An Overview from Data Preparation to Training, Evaluation, and Prediction

When you start learning machine learning, you encounter many terms such as "features," "loss functions," "gradient descent," and "overfitting."Even if you look up the meaning of each, if you don't ...
BIOENGINEER

Adversarial Attacks Distort Explainable AI Reasoning in Network and Malware Detection

A systematic study reveals that gradient-based adversarial attacks can significantly distort explainable AI feature rankings ...
umass

Coarse Gradient Descent Method and Quantization of Deep Neural Networks

Quantization is an effective approach to accelerate deep neural networks by restricting their weights and activation functions to low precisions. However, the training objective (loss function) ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

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 ...
Harvard Business School

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

Neel, Seth, Aaron Leon Roth, and Saeed Sharifi-Malvajerdi. "Descent-to-Delete: Gradient-Based Methods for Machine Unlearning." Paper presented at the 32nd Algorithmic Learning Theory Conference, March ...
JSTOR Daily

Optimization and Learning via Stochastic Gradient Search

Your institution does not have access to this book on JSTOR. Try searching on JSTOR for other items related to this book. Gradient-Based Methods for Deterministic Continuous Optimization Chapter One ...