<ul><li>Decision-Focused Fine-tuning (DFF) is a novel framework that combines decision-focused learning (DFL) with the predict-then-optimize (PO) approach.</li><li>DFF addresses challenges such as deviation from physical significance and non-differentiable or black-box models.</li><li>It maintains the proximity of the DL-enhanced model to the original predictive model within a defined trust region.</li><li>DFF demonstrates improved decision performance and adaptability to a broad range of PO tasks in diverse scenarios.</li></ul>

DFF: Decision-Focused Fine-tuning for Smarter Predict-then-Optimize with Limited Data

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