Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes

Neural Information Processing Systems 

Reducing the variance of the gradient estimator is known to improve the convergence rate of stochastic gradient-based optimization and sampling algorithms.

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