Online Algorithms for Rent-Or-Buy with Expert Advice
Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2319-2327, 2019.
We study the use of predictions by multiple experts (such as machine learning algorithms) to improve the performance of online algorithms. In particular, we consider the classical rent-or-buy problem (also called ski rental), and obtain algorithms that provably improve their performance over the adversarial scenario by using these predictions. We also prove matching lower bounds to show that our algorithms are the best possible, and perform experiments to empirically validate their performance in practice