Online Algorithms for Rent-Or-Buy with Expert Advice

@InProceedings{pmlr-v97-gollapudi19a,
  title = 	 {Online Algorithms for Rent-Or-Buy with Expert Advice},
  author =       {Gollapudi, Sreenivas and Panigrahi, Debmalya},
  booktitle = 	 {Proceedings of the 36th International Conference on Machine Learning},
  pages = 	 {2319--2327},
  year = 	 {2019},
  editor = 	 {Chaudhuri, Kamalika and Salakhutdinov, Ruslan},
  volume = 	 {97},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {09--15 Jun},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v97/gollapudi19a/gollapudi19a.pdf},
  url = 	 {https://proceedings.mlr.press/v97/gollapudi19a.html},
  abstract = 	 {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}
}