This Github repository contains a Jupyter Notebook that implements the stochastic gradient descent algorithm, a popular optimization algorithm used in machine learning for training various models. The ...

We are interested here in stochastic gradient descent algorithms, which are used to minimize functions with suitable smoothness properties. For a machine learning problem, we are looking for ...

We propose a stochastic gradient descent based optimization algorithm to solve the analytic continuation problem in which we extract real frequency spectra from imaginary time Quantum Monte Carlo data ...

One example is stochastic gradient descent, the main algorithm used to train neural networks ... affect the training dynamics of neural networks, leading to a phase diagram with distinct dynamical ...

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: Based on stochastic gradient descent, this paper presents a fast distributed stochastic Nesterov gradient descent algorithm denoted by SFDGND, which can effectively solve the problem of ...

Deep CNN is trained using the proposed Stochastic Gradient Descent–Whale Optimization Algorithm, which is the unification of the standard stochastic gradient descent algorithm with whale optimization ...

We propose a new method, S2GD (Semi-Stochastic Gradient Descent), which runs for one or several epochs in each of which a single full gradient and a random number of stochastic gradients is computed, ...