Junxuan Shen

Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems

We examine the problem of designing learning-augmented algorithms for metrical task systems (MTS) that exploit machine-learned advice while maintaining rigorous, worst-case guarantees on performance. We propose an algorithm, DART, that achieves this dual objective, providing cost within a multiplica…