Online Variance Reduction for Stochastic Optimization
conference on learning theory, 2018.
Modern stochastic optimization methods often rely on uniform sampling which is agnostic to the underlying characteristics of the data. This might degrade the convergence by yielding estimates that suffer from a high variance. A possible remedy is to employ non-uniform importance sampling techniques, which take the structure of the dataset...More
PPT (Upload PPT)