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cs.LG2024
Multiple Importance Sampling for Stochastic Gradient Estimation
Corentin Salaün, Xingchang Huang, Iliyan Georgiev +2
We introduce a theoretical and practical framework for efficient importance sampling of mini-batch samples for gradient estimation from single and multiple probability distribution…
cs.LG2023
Online Importance Sampling for Stochastic Gradient Optimization
Corentin Salaün, Xingchang Huang, Iliyan Georgiev +2
Machine learning optimization often depends on stochastic gradient descent, where the precision of gradient estimation is vital for model performance. Gradients are calculated from…