Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple.

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning.

Ayyoun is a staff writer who loves all things gaming and tech. His journey into the realm of gaming began with a PlayStation 1 but he chose PC as his platform of choice. With over 6 years of ...

Amplifying words and ideas to separate the ordinary from the extraordinary, making the mundane majestic. Amplifying words and ideas to separate the ordinary from the ...

The first chapter of Neural Networks, Tricks of the Trade strongly advocates the stochastic back-propagation method to train neural networks. This is in fact an instance of a more general technique ...

Abstract: In the context of infinite-horizon general-sum linear quadratic (LQ) games, the convergence of gradient descent remains a significant yet not completely understood issue. While the ...

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Abstract: Based on Stochastic Gradient Descent (SGD), the paper introduces two optimizers, named Interpolational Accelerating Gradient Descent (IAGD) as well as Noise-Regularized Stochastic Gradient ...