NeurIPS 2018poster363 citations
Improving Online Algorithms via ML Predictions
Manish Purohit, Zoya Svitkina, Ravi Kumar
Abstract
In this work we study the problem of using machine-learned predictions to improve performance of online algorithms. We consider two classical problems, ski rental and non-clairvoyant job scheduling, and obtain new online algorithms that use predictions to make their decisions. These algorithms are oblivious to the performance of the predictor, improve with better predictions, but do not degrade much if the predictions are poor.
BibTeX
@inproceedings{NEURIPS2018_73a427ba,
author = {Purohit, Manish and Svitkina, Zoya and Kumar, Ravi},
booktitle = {Advances in Neural Information Processing Systems},
editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Improving Online Algorithms via ML Predictions},
url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/73a427badebe0e32caa2e1fc7530b7f3-Paper.pdf},
volume = {31},
year = {2018}
}