Almost all the machine learning algorithms are based on mathematical operations. Similarly, the gradient descent method in machine learning comes from mathematics where it can be utilised for ...

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of ...

Abstract: This paper addresses a unified convergence analysis for a large family of stochastic gradient projection algorithms for dealing with constrained finite sum convex problems, with a smooth ...

Abstract: This paper targets developing algorithms for solving distributed learning problems in a communication-efficient fashion, by generalizing the recent method of lazily aggregated gradient (LAG) ...

Gradient descent is a method to minimize an objective function F(θ) It’s like a “fitness tracker” for your model — it tells you how good or bad your model’’ predictions are. Gradient descent isn’t a ...

This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. The core idea of the algorithm is based on building models with local stochastic ...