2 papers
cs.DS2026
Learning-Augmented Approximation for Unrelated-Machines Makespan Scheduling
Kaito Baba, Evripidis Bampis, Giorgos Mitropoulos
Recently, Antoniadis et al. (ICLR 2025) proposed a framework for incorporating predictions to approximate NP-hard selection problems. Despite its simplicity, this approach tightly…
cs.DS2025
Polynomial Time Learning-Augmented Algorithms for NP-hard Permutation Problems
Evripidis Bampis, Bruno Escoffier, Dimitris Fotakis +2
We consider a learning-augmented framework for NP-hard permutation problems. The algorithm has access to predictions telling, given a pair of elements, whether is before…