Si-Zhe Li

Compressing Value Predictions for Learning-Augmented Metrical Task Systems

This work introduces landmark-compressed value predictions, in which the predictor reports predicted dual values only at $m$ landmarks and the remaining values are reconstructed by a Lipschitz extension.