Online Algorithms for Rent-Or-Buy with Expert Advice

Sreenivas Gollapudi, Debmalya Panigrahi
Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2319-2327, 2019.

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

Cite this Paper

BibTeX
@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} }
Endnote
%0 Conference Paper %T Online Algorithms for Rent-Or-Buy with Expert Advice %A Sreenivas Gollapudi %A Debmalya Panigrahi %B Proceedings of the 36th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2019 %E Kamalika Chaudhuri %E Ruslan Salakhutdinov %F pmlr-v97-gollapudi19a %I PMLR %P 2319--2327 %U https://proceedings.mlr.press/v97/gollapudi19a.html %V 97 %X 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
APA
Gollapudi, S. & Panigrahi, D.. (2019). Online Algorithms for Rent-Or-Buy with Expert Advice. Proceedings of the 36th International Conference on Machine Learning, in Proceedings of Machine Learning Research 97:2319-2327 Available from https://proceedings.mlr.press/v97/gollapudi19a.html.

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