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 ...

Autograd is a python package that can provide us with a way to differentiate Numpy and Python code. It is a library for gradient-based optimization. Using this package we can work with a large subset ...

Gradient descent is a fundamental optimization algorithm widely used in machine learning and numerical optimization. It is employed to minimize a cost function iteratively by adjusting the parameters ...

Abstract: A loss function has two crucial roles in training a conventional discriminant deep neural network (DNN): (i) it measures the goodness of classification and (ii) generates the gradients that ...

Abstract: In this article, we propose a distributional policy-gradient method based on distributional reinforcement learning (RL) and policy gradient. Conventional RL algorithms typically estimate the ...

This repository contains the code from the paper Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value Function (Clément Bonnet, Laurence Midgley, Alexandre Laterre) published at ...