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Hao-Jun Shi

2 accepted papers

2026

Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent

ICML 2026poster

To maximize hardware utilization, modern machine learning systems typically employ large constant or manually tuned batch size schedules, relying on heuristics that are brittle and costly to tune. Existing adaptive strategies based on gradient noise scale (GNS) offer a principled alternative. Howeve…

Cited by 0SourceScholar
2018

A Progressive Batching L-BFGS Method for Machine Learning

ICML 2018oral

The standard L-BFGS method relies on gradient approximations that are not dominated by noise, so that search directions are descent directions, the line search is reliable, and quasi-Newton updating yields useful quadratic models of the objective function. All of this appears to call for a full batc…

Cited by 214SourcePDFScholar