Recently, Antoniadis et al. (ICLR 2025) proposed a framework for incorporating predictions to approximate NP-hard selection problems.
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arXiv:2606. 18807v1 Announce Type: cross Abstract: The field of learning-augmented algorithms has demonstrated that machine-learned predictions can bypass worst-case lower bounds across a wide range of problems.
arXiv:2606. 05380v1 Announce Type: cross Abstract: We present learning-augmented algorithms for two general classes of online minimization problems: metrical task systems and laminar set cover.
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arXiv:2606. 01342v1 Announce Type: cross Abstract: Learning-augmented paging has been extensively studied in recent years.
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