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Joseph Keslin

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#machine learning Preprint Oct 2026

Strong Gaussian Approximation of Constant Learning Rate SGD: Bias and Trajectory Inference

This paper develops strong Gaussian approximations (KMT type) for constant learning rate stochastic gradient descent (SGD). We work with heavy tailed noise and assume that the number of iterates grows and the learning rate shrinks simultaneously. Our work constructs simple Gaussian processes on the same space and bound...

Joseph Keslin, Wei-Biao Wu · 0 citations

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