AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems
AdaSwitch is a meta-algorithm for online problems where future requests are only partially predictable. It introduces a bounded-influence framework, allowing the algorithm to adaptively switch between conservative online actions and predictive offline actions. This results in explicit performance guarantees that improve as prediction errors decrease or optimal solutions become larger.