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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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0111 · Nov 202419922001200920172026
2 results for “noise-reshaping”
Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD?cs.LG

SignSGD outperforms SGD in linear regression with optimal scaling laws under PLRF model.

problem Improving linear regression performance with signSGD under power-law random features.
method Analysis of signSGD risk under PLRF model, comparison with SGD, identification of unique effects.
result SignSGD can have a steeper compute-optimal slope than SGD in noisy regimes, especially with WSD schedule.
signSGDlinear regressionscaling lawspower-law random featuresnoise-reshaping
2026-03-02abs ↗pdf ↗
Exact Risk Curves of signSGD in High-Dimensions: Quantifying Preconditioning and Noise-Compression Effectsstat.ML

SignSGD analysis quantifies its effects in high dimensions.

problem Understanding signSGD's effects in high-dimensional settings.
method High-dimensional analysis of signSGD, deriving SDE and ODE for risk.
result Quantification of signSGD's effects: effective learning rate, noise compression, diagonal preconditioning, gradient noise reshaping.
signSGDhigh dimensionsrisk curvespreconditioningnoise compression
2024-11-19abs ↗pdf ↗