An Asymptotic Analysis of Random Partition Based Minibatch Momentum Methods for Linear Regression Models
An Asymptotic Analysis of Random Partition Based Minibatch Momentum Methods for Linear Regression Models
Momentum methods have been shown to accelerate the convergence of the standard gradient descent algorithm in practice and theory. In particular, the minibatch-based gradient descent methods with momentum (MGDM) are widely used to solve large-scale optimization problems with massive datasets. Despite the success of the MGDM methods in practice, their …