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 ...
GitHub

[Docs] - Supplying gradients from an external, non-torch function

We've been using Bayesian optimization (with GPyOpt) for molecular geometries. I'd like to migrate to BoTorch and as a non-expert, I'm hitting some walls with the current docs. Yet... I'd like to ...
Scientific Research Publishing

Vanishing Gradients in an Artificial Deep Neural Network: The Impact of Activation Functions and Optimization Techniques ()

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 the ...
IEEE

Leveraging Simplex Gradient Variance and Bias Reduction for Black-Box Optimization of Noisy and Costly Functions

Abstract: Gradient variance errors in gradient-based search methods are largely mitigated using momentum, however the bias gradient errors may fail the numerical search methods in reaching the true ...
GitHub

Gradient Monte Carlo Prediction

This project implements gradient Monte Carlo prediction for estimating value functions in a random walk environment. It compares different function approximation strategies using a 1000-state domain.