Uncertainty Quantification for Online Learning and Stochastic Approximation via Hierarchical Incremental Gradient Descent

13 Feb 2018 Weijie J. Su Yuancheng Zhu

Stochastic gradient descent (SGD) is an immensely popular approach for online learning in settings where data arrives in a stream or data sizes are very large. However, despite an ever- increasing volume of work on SGD, much less is known about the statistical inferential properties of SGD-based predictions... (read more)

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METHOD TYPE
SGD
Stochastic Optimization