A self-normalized subsampling method builds asymptotically valid confidence regions for Polyak–Ruppert averaged SGD under finite- or infinite-variance gradient noise.
Stochastic differential equations models for least-squares stochastic gradient descent.arXiv preprint arXiv:2407.02322, 2024
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Statistical Inference for Stochastic Gradient Descent: Beyond Finite Variance
A self-normalized subsampling method builds asymptotically valid confidence regions for Polyak–Ruppert averaged SGD under finite- or infinite-variance gradient noise.