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cs.LG2025
Global Dynamics of Heavy-Tailed SGDs in Nonconvex Loss Landscape: Characterization and Control
Xingyu Wang, Chang-Han Rhee
Stochastic gradient descent (SGD) and its variants enable modern artificial intelligence. However, theoretical understanding lags far behind their empirical success. It is widely b…
cs.LG2021
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise
Xingyu Wang, Sewoong Oh, Chang-Han Rhee
The empirical success of deep learning is often attributed to SGD's mysterious ability to avoid sharp local minima in the loss landscape, as sharp minima are known to lead to poor…