Author

Junyi Ye

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#machine learning Preprint Aug 2026

Can You Delete a Year of Market Data? Machine Unlearning Against Exact Retraining Oracles

This work benchmarks temporal unlearning with 3,200 paired references trained on all data and oracles retrained without the requested period, finding that across twelve deployable architecture-method pairs, only TSMixer with the hinge method remains near the oracle in every fold, closing 74-118% of the reference-to-ora...

Junyi Ye · 0 citations

Preprint Aug 2026

Regime-Gated Residual Mixture-of-Experts for Cross-Sectional Volatility Forecasting

This paper proposes RG-ResMoE, a regime-gated residual mixture-of-experts architecture in which regime information is used only for expert routing rather than for direct forecasting, which consistently outperforms a capacity-matched MLP in both forecasting accuracy and training stability in the main U.S. study.

Junyi Ye, Gargi Vijay Borde · 0 citations