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University of Michigan -Ann Arbor, University of California San Diego
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LLM-guided program discovery gets a serious boost: evolving programs across related tasks isn't just faster, it also beats overfitting, especially when data is scarce.
Transformers can directly solve quadratic programs and leverage covariance matrices for superior decision-making, outperforming traditional "predict-then-optimize" methods in portfolio construction.
